{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签\n",
    "plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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sYO/evVy7di1Lv4/9+/czduxYjhw5kmMn7v/6+eef2bRpE8ePHyctLY127drRvXt3GjduTFxcHIcPH2bo0KFcuHABACcnJ0D3d7927Vr++usvrl27Rr9+/WjcuDHe3t7Mnj0bX19fPv74Yz777DOGDBlCnTp1spXt5eVFRETEE2MURYMkHEXco1+r6enpWFtb880336BSqbCysiIjI4MHDx4AsGHDBoYNG8b06dNJTU3l1q1bVK9eHUtLS3bs2MGDBw84e/YsarWamTNnsnv3bpo0acKBAweIi4tjyJAhWFpa8ueff+oTjgMHDtChQwd97cSWLVvw8fEBdF+g33//PVWrVmXQoEFMmzaNYcOGce7cOV544QV9/CdPnqRUqVLUrl0b0I1OKV++PGlpaYDuy+hRLUflypVJSUkhKSmJypUrExMTQ0BAAPb29hw7dixbM9Arr7zCDz/8oE84Tp8+zciRI3N8HyMiInj77bf1X3b/1q9fvyx9QZ5WXFwcy5YtY//+/VhYWLBkyRLs7OwYNWoU165dIzk5mY8//hhbW1v+/PPPLKMe5s2bR9WqVWnRogWBgYEsX76cSpUq4eXlpT/nzp07BAUF0aFDBwBatGjBW2+9pX8P09PT9TUq/fr1w8rKipSUFCpXrkxSUpK+KeORGzduULVqVUBX2+Dq6vrY12dra8uIESMoXbq0PlEJCgqiSZMmDBw4kH79+nHp0iU2b95M9erV9f9vAgICOHHiRK73/e8X+ptvvsnSpUsfG8vjrF+/Hmtra8zNzenatSsTJkxg7NixREdH61+vWq1m/fr1WUb3WFhYMHfuXP3ztm3bcu7cOWxtbUlOTqZBgwb6zpgrV66kT58+T4zF0dGRhISEXI8/6hfTsGFDDh48qP83+PPPP5kyZUq2ZCM9PZ21a9eyf/9+0tPT+f7771EUBUVRsr2PZmZmjx2l9Mhrr73Ga6+9RkpKCufPn8fc3JzLly/TpEkTfQ3boz4h/7Z8+XJGjx6Nr68vvr6+1K9fn+3btzN06FAqVqzI2LFjefXVV/W1mjlJSEjQJzCi6JOEoxgIDAwkISEBBwcHPv/8c7Zu3Urp0qW5cOGCvvq3Q4cObNy4kalTp+p/HV69elXfxwN0tQ4ajQZ/f3/Gjx8P/PNlkJGRoa8+faRPnz76L3O1Wk39+vX1916wYAGWlpa0b9+e8uXLs27dOuzs7BgwYABnz57V3+OXX34hKCiIw4cPo1Kp6NKlC126dCEzM5MxY8YwevRoLCwsUKlUhIeHZ+vD8UiNGjWydVrr3r077777Lnfv3iUtLY34+HhatmyZ43tobm7OhQsXiI+Pz3bsUW3Qf/3xxx80adIky5f+47i4uHDt2jUyMzPJyMjI8ouuevXqfP3114DuV7yLiwuenp4AnD17lhUrVjBp0iQCAwNZuHAh1atXp02bNgwePFjfbHbgwAGGDBnCpUuX8PDwoGrVqnzzzTeALuHs27cvTZs2RaVSsWrVKn0fjvDwcBYvXsz+/fuzxBsYGIifnx+gS5aelHCAbuSLhYWF/v0yMzPTj4Z59H/D0tIyy/u5Y8cOVCpVtlqLVq1aMXLkyCxf3P+dn2HPnj24urpSv379J8YGusRpzJgxjB07lilTpvDJJ5+QnJzMggULiIqK4rvvvgN0TXtvvfUWzs7OWRIxRVEYMGAAP/zwA0eOHNHvf9o+HLVr12br1q2P7aPg7u7OgAEDmDBhAgsWLCA5OZlPP/1UP5Ln3/r27UtwcDB2dnaMHTuWF198ET8/P+Lj4/UJR1paGnFxcXh5edGhQ4fHDhkHXT+nt956i6ioKJo1a4a9vX2emnlu3brF6NGjGTduHKDrQ/XvJpx33nmHzz//nFGjRmXpJP1vx48f1/+IEUWfJBxF3LZt21i2bBmtW7fG39+fyMhIJk2axMCBA6lQoYL+V7+dnR3+/v5MmzYNMzMzfVXwwIEDee+992jRogVarRaNRpPtgz80NJSuXbtmGU2RkJBAQEAAFhYW+tEEQ4cO5fPPP0er1bJ8+XKWLFmibxLo1KkTs2bNol27dvovMdBVu9asWZPFixfz7rvvsn//fi5evKifa6B27doMHDjwqSbucnNzw9fXl127dgHQrFmzxzaL7Ny5M8cREblNQnby5EmWLFmSr/kCbGxsqFSpEhqNRl9rcu/ePQ4fPqwfspqRkYG/v78+GVy6dClTp07VJxbNmzfn1KlT+i/FR01X/fr1Y8mSJXz88cesWLGCkJAQjh8/TmhoKJcvX+btt9+mbt26eXovNRoNf/31l76JKq8Jh0qlonnz5vrOwf+exyI3//1lDLrh0ebm5jz33HN88sknfPXVV7i4uGQbEhoaGspPP/3E2bNn81QLtWfPHho1akS3bt2YMmWKvhPtmjVr2Lhxo/48b29vPvvsM4YNG0ZISIj+b+KPP/7g5MmTBhs506VLF4YPH64fpZObiRMn0qJFC+bPn8/u3bvp3bu3fpTVv82fPx8PDw/effdd/b5t27axYMECpk6dipmZmb5JJa9DTkeMGEHnzp31/z+bNGmS5biZmVmOHaArVKjAl19+qe9QnpqammWI9RdffEGbNm345ZdfGDVqlD7BfkSr1fLdd9/lOB+PKJqk02gRFhkZSXh4ODt37mT//v00aNCAjIwMvvjiCxo1asS9e/f0TROg+2VZu3Zt+vfvz/Xr1/H29sbW1pYpU6bQr18/+vbtS+/evbNNztSwYUOioqKIiIggPDyc8PBwHB0d2b9/P+Hh4dy4cYPbt2/rh5aamZlx5MgR/P399feIi4tj1qxZjBo1Ksu9XVxcGDlyJLNmzUKr1bJz504OHz6Mt7c3oPuwHDNmTK6TP+X05fmoChl0TRFt27Zl9+7dWX5d5XS/7t27884772R75DYPxejRozlw4ACrV6/O8Xhubt68qf+3Cw8Pp0OHDsyYMUP/PDIyMkvN05w5cxgyZEiWe4wfP5733nsv21DdL774gjVr1hAWFkZISIi+ZsnZ2ZkvvviCP/74I0/v5aZNm7Czs9P3L4iNjdUnHMuWLUOlUlGuXLkc3/8ff/yRzz//XF/b9ujeeUl0UlNTGT58OKtWrWLdunVYW1tz8+ZNatWqla2PCuh+Jd+/f5/Zs2c/8d6gq5V7NE/JI3PmzKFKlSq0aNEiy/4RI0YQFxfHH3/8AegmVZs8eTKTJ0822Jws1tbWTJ48mQEDBjx2dk17e3smT57M8OHDOX/+fJbRQf9WsWLFbImXi4sLq1evZsaMGU8VY2JiIhkZGdy6dYuJEydy6tSpLP+HqlSpwu3btwkMDOTatWsEBgYCumH7y5YtIyMjg9TUVF588UV9cnzq1Cl+++03VqxYwYABAxg+fHi2cidOnEiNGjX0Tbii6JOEowirUaMG27ZtIyQkBK1WS+vWrZk3bx5hYWGcPn2a9PR0kpKSsn0AWVhYZNk3f/58Tpw4wZkzZ7h48SKdO3fWH0tPTyc1NTVPXxaP5sh4VAbofq1nZmaSnp7ORx99RIsWLVi/fj2BgYH62oYPP/yQ48ePY2ZmxvTp01m5ciUjRowAdL+SLCwsyMzMxNnZmYEDB3L48GGcnZ2zTVn+qEPh5cuX9e3T7dq1w8vLi2XLlvHVV1/pq/vfeuutbPG7urri4eGR7ZFb57+yZcvSv39/Pv300yyJXW4ete/nZVKozMxM/bDQR+U/ei8zMjLo3Lkzo0aNYtu2bezcuVP/XrZo0YJr167h7e3NSy+9xNatW5k8eTJlypTB3d0dOzs7MjIy6NatG5UrV8bCwgJnZ2eGDx+ufy+TkpL0zVkJCQkcOXKEXbt24e3tTUZGBn379uXOnTtcuHAhWw2GVqtlxYoVnDt3jjNnzjBkyBDMzMwoU6YMo0ePRlEU4uLisjVRpaSksGjRImrVqqUfEVW+fHnKlSvHpk2bmDNnDu+88w6vv/66vl8S6L6wBw8ezNSpU/M8isjCwkL/XgL4+Pgwc+ZM/Zfgo/fSwcGBwMBAfdPd3Llz0Wg09O/f/7HJgaIoqNXqPNfKvf3229SsWZNu3bplm4wrKiqK1atX07NnTyZOnMiaNWvo2LEjtWvXZuTIkWzcuJHQ0FB9f5/U1FR2797N5cuX9X/j9vb2/P7777Rq1YorV65w6tSpPHVofeTrr79m7dq1+Pn5ERUVxQsvvKBPKkD3Nzp9+nTat2+Pv78/R48eBWDs2LH4+vrSqlUrWrduTdeuXRkyZAiZmZm89957jBs3Dg8PD7788ksOHjyoT04BPv/8c3bt2sUPP/yQ5zhFEaCIIk2r1SoNGzZUfvrpp2zHBgwYoJiZmSnvv/++sn37dqVevXpKixYtlHLlyin16tVTnnvuOaVChQr67UePpk2bKgEBAYqiKMqiRYsUNzc3pUKFCoqXl9djHx4eHsrAgQOzxTB//nz987S0NKVmzZpKnz59lHv37uX6uhISEhRASUhIUNLT05Wc/qsOGDBAmTdvnv756dOnFWdnZ0Wr1SoZGRmPfc8eHe/QoYPSpEkTpUGDBspzzz2ntGnTJtvDz89PadmypdKgQQNlz549We4VEhKibN++Pdey/ntumTJlFE9Pzye+l56enkr16tWzXL9o0SKlT58+Wfa9/PLLSkBAgHL8+PHHlt2gQQNl06ZNiqIoSosWLZR9+/Zlu/eLL76oKIqizJgxQ/H19VXS09OVqKgopWbNmsrbb7+tqNVqZdGiRcqbb76pKIqi3L9/X+nSpUuW+7Rs2VI5deqUoiiK8sYbbyh+fn7KiRMnFEXRve/VqlVTKlWqpAQFBemv+fvvvxUPDw+lZcuWyu7du3N9DWFhYUrfvn2V+/fvZ9l/9+5dZeXKlYpWq33se/BvV69eVUqXLp1l3+zZs5X69esrv/76a7bzY2JilFKlSilLlixRFEVR2rVrp9ja2ipOTk6Kk5OT4uDgoDg5OSmOjo6KtbW1YmZmpgQGBuY5HkVRlN9//13RaDSKoihKcnKy0qhRI6VUqVLKyy+/rGzZsiXL6wsPD1cmTZqkNG3aVLG1tVUWLFigKIqiZGZmKrVr11Y6dOigREZGZitj1KhRioeHR5a/ycLozz//VJKTk00dhjAwlaIUslW7RL7dvXs3x+GOV65cydY5sai6desWFSpUMHUYxUJ0dDSOjo6PHVr6aBjss1ByGBmRkpKSY/+HmJiYLNN6F0aBgYHUqVPHYM0pTxIbG4uTk9MTayO0Wi2KouSr1kIIU5CEQwghhBBGJ304hBBCCGF0knAIUYRs3LiRKlWqYGFhQb169bItlZ6TAwcOULt2bcqUKZNtNMfatWvx8vLC09OTlStX5iuW3bt34+Pjo1+DRQghHkcSDiGKiOvXrzNo0CBmzJhBZGQkNWrU0K+Um5vo6Gh69OhB//79OXbsGCtWrGDfvn0ABAcH6yeU2rlzJxMnTuTy5ct5ikV5OBX7o0X5pGVWCPEk0odDiCJiy5Yt3L59m/feew/QLarXtWvXbEMp/23u3Ln8/PPPhISEoFKp2LhxI3/88Qe//fYbI0eOJDQ0VD9x2XfffUd0dLR+gqfH2blzZ5YZOHfs2EHHjh2f8RUKIYozqeEQoojo1q2bPtkAuHz5MtWrV3/sNefPn6dt27b60SJNmjThzJkz+mPt2rXTn/vvYzlRq9UkJCQQHx/PuHHj9KOizMzMmDBhgtRyCCEeSxIOYRDpmVr8v/iLymO3cvRa9pU2hWGlp6fz7bff6pf4zk1CQoJ+1lbQLRZ2+/btJx7LyfTp03FycsLZ2ZnAwED9xFZarZZTp07x119/PctLEoVVWgIJ02rCZCf2fvuGqaMRRZgkHMIgrCzM6FzXA4DNF+6YOJrib9KkSdjb2z+xD4eFhUWW+TZsbGz0TTCPO5aTcePG8eDBA+rXr59tzgdzc3Op5SimlL8+xzE9ihvasqS0yXlKdSHyQhIOYTDd/XWLL20PvkOGJv+LrYm82bt3LwsWLOD3339/4oJlrq6uREdH658nJibqJ6563LGcWFtbc/z4cQIDA7OtFqrRaKSWozi6thvV2WUAfKYMoa2v9xMuECJ3knAIg2nq7UoZBysepGRwRJpVjCIsLIz+/fuzYMGCPC3b3bhxY44dO6Z/HhgYSPny5Z94LCeKojBhwoRsM9o+In05ipnUB7DxQwB+yeyEY6022FvLAuPi6UnCIQzGwtyMLr66JbY3n5dmFUNLTU2lW7du9OzZk969e5OUlERSUhKKopCQkJDjgmI9evTgyJEj7N69m4yMDGbOnKkfTdKnTx9WrVpFUFAQSUlJzJs377EjTdLT07l582aui5JptVoiIiLytCS9KAJ2fgaJt4lQlWNm5it09/N88jVCPIYMixUGdSo8lpd/OkYpawtOfd4eG0tZ38FQNm7cSK9evbLtDwsLIyAggLlz5+Z4/KeffmL48OE4ODjg7OzMsWPHcHd3B+Czzz7jm2++wcbGhurVq3Po0CH9aqk5iYiI0DfDJCUl0aZNGw4cOICDgwOgW0FX1rwpBq7shN/7oqDiJfVEQi19ODPhBfl7Fs9EEg5hUFqtQosZe4lKSGPh6w3pUMfD1CEJdElJaGgorVq10icHj4SEhBAZGUmbNm3ytTBZQkICTk5OxMfH4+joaOiQhamkxsEPzSHxDsfK9qP/zR70qufJ3H71URSFzMzMbH14RNFjbm6OhYVFtgUWjUka5IRBmZmp6OZXjsWHw9h84Y4kHIWEt7d3liGw/+bj45On/iCihNgxDhLvoJSuxqexPQBdh/D09HTu3Lnz2JFMomixs7OjXLlyBbYCsiQcwuC6+3uy+HAYu0PukpKeiZ2V/DcTokgI3QbnV4LKjODGM4jYkI6jjQXPVS1NWNh1zM3N8fT0xMrKqkB/GQvDUhSF9PR0oqOjCQsLo3r16rl2Bjck+SYQBudXwYlKrnbcjE1hb+g9uklnMyEKv5RY2DJSt938A1bd8QBu0qmuB2gz0Wq1VKxYETs7O1NGKQzE1tYWS0tLbty4QXp6OjY2NkYvU0apCINTqXTNKgCbz+c+c6UQohDZ/ikk3YUyNchoM47twVHAP/PrAAXyK1gUnIL+95T/PcIoHn1I7bscTWJa9uGaQohC5NJmCPoDVGbQ6yeO3kgmNjmd0vZWNK9S2tTRiWJCEg5hFLU8SlGtrAPpmVp2hdw1dThCiNwk34cto3Tbz42ECg3Z8rBmsotvOSzM5WtCGIb8TxJGIc0qQhQR2z6B5Ghwqw0BY1FnathxUdec8uhvWAhDkIRDGM2jZpVDV2OITZbZJ4UodC6uh4t/gsocev8IFtYcuBxNYlom7o7WNK7sauoIRTEiCYcwmqpuDtQt70imVmHrBanlEKJQSYqGrR/rtluOAs/6AGw4FwlAD39PzMxk6KuhREREEBAQgI+PD35+fvzxxx+mDqnAScIhjKpXPd1iYBvOScIhRKGhKLD1I0i5D+51oc0YABLSMth96R4AvernvpCfyD8LCwvmzp1LSEgIf/31FyNHjiQ5OdnUYRUoSTiEUfXw98RMBWduxHHzvsxQKEShcPFPuLQJzCyg1w9goZtpckdQFOmZWqqXdcCnnExXb0jlypWjXr16AHh4eFCmTBliY2NNG1QBk4RDGFVZRxueq1YGgI0Pq2qFECaUdA+2fqLbbvUJlPPXH3rUnNKrfnmZSdSIzpw5g0ajoWLFiga978GDB+nevTuenp6oVCo2bNhg0Ps/K0k4hNH1fNissv5cJLJWoBAmpCi6IbCpseDhC60+1h+Kik/j2N/3AehZT2YHNpbY2FjeeOMNFi5cmKfzAwICWLp0aZ7OTU5Oxt/fnwULFjxDhMYjCYcwuo513LGxNOPv6GSCIxNMHY4QJVfQWgjdAmaW0OtHfVMKwKbzkSgKNKnsSgWX4jV9eYUKFfjhhx+y7Dt69Ch2dnbcuHHDIGWsXLkSW1tb7ty5o983aNAg/Pz8iI+PB0CtVtOrVy/Gjh1LixYtDFLuv3Xu3JkpU6bQu3dvg9/bECThEEZXysaS9rXdAVgfKM0qQphEYpRuzg3QdRL18M1yeH2grmN3z/p5q91QFIWU9EyTPPJbU9q0aVNOnTqVJfaRI0cyatQovLy8spw7bdo0HBwcHvu4efNmtjL69etHjRo1mDZtGgCTJk1i9+7dbN++HScnJxRFYeDAgbRr147XX389X/EXF7J4mygQveuXZ8uFO2y+cJvxXWrJ7IVCFCRFgc0jIe2Brs9Gy5FZDl+OSuTSnQQszVV09c3bZF+pGRp8Ju40eKh5EfJlx3ytQt2sWTOWLVumf758+XIiIiIYN25ctnMHDx5M3759H3s/T8/sSZlKpWLq1Km89NJLeHh4MH/+fA4dOkT58rom5SNHjrB69Wr8/Pz0fSuWL1+Or69vtnsVV5JwiALRuoYbLnaWRCeqOXr9Pq1ruJk6JCFKjgur4cr2h00pP4G5ZZbDjzqLBtQsi7OdVU53KNKaNWvG2LFjSUpKQqVSMX78eKZMmYKDg0O2c11dXXF1fboJz7p164aPjw9ffvklf/31F3Xq1NEfa9myJVqt9on3mDZtmr6WBCA1NZXjx4/zwQcf6PeFhIRQqVKlp4rRlCThEAXC0tyMbn6eLD9+gw3nIiXhEKKgJNzWrQQL0HYcuPtkOazVKmx6OE9O73zMvWFraU7Ilx0NFmZ+2Fqa5+v8hg0bYmZmxtmzZ9m9ezdubm4MGjQox3P/+4Wfk9y+8Hfs2EFoaCgajQZ3d/d8xfjIf2tYBgwYQJ8+fXjxxRf1+3KqYSkKJOEQBaZXfV3CsTM4itReGmyt8vehIYTIJ0WBzSMgLR48G0CLEdlOORUeS+SDVEpZW9CuVtk831qlUuWrWcOU7Ozs8PX1Zd26dSxatIht27blujT70zapnD17lr59+7JkyRKWLl3KhAkTnmo20f/WsNja2lK2bFmqVauW73sVNkXjf4soFhpUcqGiqy0RsansunSXHv5FM0sXosg4twKu/gXmVrpRKebZP/IfzQLc2dcDm3zWHBQlzZo1Y/78+fTs2ZOAgIBcz3uaJpXw8HC6du3K+PHj6d+/P1WqVKF58+acPXuWBg0aPGPkeZeUlMS1a9f0z8PCwjh37hyurq6FoglGeu6JAqNSqf6Z6lxGqwhhXPG3YMfDTpFtP4OytbKdos7U6Nc5evS3WVz5+/tjaWnJrFmzDHrf2NhYOnXqRM+ePRk7diygGxXTuXNnxo8fb9CynuT06dPUr1+f+vV16+J89NFH1K9fn4kTJxZoHLmRGg5RoHrWK8/8vdc4cCWamCQ1ZRysTR2SEMWPosCm4aBOgAqNocWHOZ62L/QeCQ9Xhm1apXQBB1mwVq1axQcffGDwpglXV1dCQ0Oz7d+6datB7r9///48nxsQEFCoJ1eUGg5RoKqVdcC/ghMarcJGWdBNCOM4+z+4vgcsbHRNKWY5N5WsPfPPVObmxXBlWK1Wy927d5k2bRpXr15l0qRJpg6pRJOEQxS4lxpWAGDtmVsmjkSIYujBTdj5mW673edQpnqOp8Ukqdl/Wbcy7EsNKhRUdAXq4MGDlCtXjt9++41169bh6CgL0pmSJByiwHX398TK3IxLdxK4eDve1OEIUXwoCmz8ANIToWJTaDY011M3nrtNplbBv6Iz1d1LFWCQBScgIACtVktISAhNmzY1dTglniQcosA521nR3kc3/G7dGek8KoTBnP4Fwg6AhS30/CHXphT4p4bxpQbFu7OoKDwk4RAm8ahZZeO5SDI0T559TwjxBHHh8NcE3Xb7SVAm986RF2/Hc+lOAlbmZnSX4emigEjCIUyidXU3yjhYcz85nf2Xo00djhBFm1ara0rJSIZKLaDJ+489/VHN4gs+7sVyKnNROEnCIUzCwtyM3g9XpVx7JsLE0QhRxJ1eAuGHwNIOei2AXGbRBEjP1OrXTunTUJpTRMGRhEOYTJ+HzSp7Q+8Rm5xu4miEKKJi/4ZdDyd2av8FuFZ57On7L+v+3so4WNO6uqxpJAqOJBzCZGp5OOJb3okMjcKmc9J5VIh80zelpEDlVtD4nSdesu6srrPoiw3KY2EuXwGi4Mj/NmFSfR72kF97VubkECLfTi6EG0fA0h56fv/YphSA2OR09obq5t7oU0zn3hCFlyQcwqR61CuPpbmK4MgEQqMSTB2OEEXH/euwe7Juu8OX4FL5iZdsOhdJhkbBt7wTNT2K59wbovCShEOYlKu9Fc/Xcgdgncw8KkTeaDWwYShkpoJ3G2j4Vp4ue1ST+GhYuhAFSRIOYXKPOo+uD7wtc3IIkRcnfoKI42DlkKemFIDQqASCIxOwNFfRQ+beECYgCYcwuYCabpRxsHq4toPMyfEkMTExeHt7Ex4e/sRzJ0+ejEqlyvZ4tAKln59flv3vvPPkTofCxGKuwp4vddsdp4JzpTxdtuaUrnbj+VruuNjL3Bui4EnCIUzO0txM34Ft1cmbJo6mcIuJiaFbt255SjYAxo4dS1xcnP5x7tw53NzcqF+/PikpKVy/fp179+7pj8+fP9+4L0A8G31TShpUbQcN3szTZWkZGv4M1CUcrzSpaMwIhciVJByiUOjbWPchuO/yPaLi00wcTeHVr18/Xn311Tyfb2Njg7Ozs/6xYMECRo4ciZOTE4GBgfj5+eHm5qY/bmtra8ToxTM7tgBunQRrR+gxH1R5W1L+r5C7PEjJoJyTjcy9UYQdPHiQ7t274+npiUqlYsOGDaYOKV8k4RCFQlU3B5pUdkWryMyjj7No0SKGDx/+VNfevn2b9evX668/efIkt27d0iccQ4YMQa1W53q9Wq0mISEhy0MUoOjLsHeKbrvjNHDKe8fP1ad0NYcvN6qIuVnekhRRcAICAli6dOkTz0tOTsbf358FCxYYPygjkIRDFBr9Hlb1rj4dgVarmDiawsnb2/upr/3pp5/o378/Dg4OAFy+fJmWLVty+PBhdu7cya5du5gzZ06u10+fPh0nJyf9o2JFqZovMJpM2DAENGqo3gHqv5bnS2/eT+HItfuoVNC3kQFHpygKpCeb5qHk7/OhQoUK/PDDD1n2HT16FDs7O27cuGGQt2PlypXY2tpy584d/b5Bgwbh5+dHfHy8Qcro3LkzU6ZMoXfv3ga5X0GzMHUAQjzSuW45Jm26SERsKsf+vs9z1cqYOqRiQ6PRsGjRIvbs2aPf99NPP2U5Z+LEicybN4+xY8fmeI9x48bx0Ucf6Z8nJCRI0lFQjs6DyDNg7QTdv8tzUwrAmtO6GsNW1d2o4GJnuJgyUmCaiUa7jL8NVvZ5Pr1p06acOnVK/1xRFEaOHMmoUaPw8vLKcu60adOYNm3aY+8XEhJCpUpZO+v269ePGTNmMG3aNObPn8+kSZPYvXs3x48fx8nJKc+xFmeScIhCw9bKnF71yrP8+A1WnrwpCYcB7du3j9KlS+Pj45PrOWXLliUyMvcp5q2trbG2tjZGeOJx7obA/um67c5fg2Pev+QzNVr+eNhE2a9xyU0OmzVrxrJly/TPly9fTkREBOPGjct27uDBg+nbt+9j7+fpmf3fQKVSMXXqVF566SU8PDyYP38+hw4donx5WSDvEUk4RKHySuOKLD9+g78u3iU2OR1XGb5nEGvWrOHFF1/Msq958+asWbNGX0tx7NixbL/2hIlpMh42paRDjU7g3y9fl++/HM3dBDWu9la0r+1u2Ngs7XQ1DaZgmb+ammbNmjF27FiSkpJQqVSMHz+eKVOm6JsX/83V1RVXV9enCqtbt274+Pjw5Zdf8tdff1GnTp0cz/tvLUpqairHjx/ngw8+0O/LqRalqJOEQxQqdcs7Ube8I8GRCawPjOTtlk/fZ6EkSUhIwNbWFktLyxyP79ixI1untDp16vD+++8zadIkQkND+fbbb4tsZ7Ri68hcuHMObJyh29x8NaUArDqlq93o06A8VhYG7rKnUuWrWcOUGjZsiJmZGWfPnmX37t24ubkxaNCgHM992iYV0P2dhYaGotFocHfPPcH7by3KgAED6NOnT5YfBTnVohR1knCIQueVxpUIjgxm9ambvPVcZVT5/JAtifz8/Jg7dy69evXKduz69evcvn2bJk2aZNn/zTffMGjQINq2bUvZsmWZNWsWb76Zt3kdRAGICob9X+u2u8wCx3L5uvxuQhr7LusWanulBDenANjZ2eHr68u6detYtGgR27ZtwyyX2Vmftknl7Nmz9O3blyVLlrB06VImTJjAH3/8keP1/61FsbW1pWzZslSrVi0fr6rokYRDFDo963kydWsIV+4mERjxgAaVXEwdUqGj/KeX/uMmAqtatSqZmZnZ9js7O7N+/XpDhyYMQZMBGwaDNgNqdgXfl/N9i7VnbqHRKjSu7EK1srJQW7NmzZg/fz49e/YkICAg1/OepkklPDycrl27Mn78ePr370+VKlVo3rw5Z8+epUGDBs8Y+T+SkpK4du2a/nlYWBjnzp3D1dW1SDS/yLBYUeg42ljS1Vf3C0JmHhUl0qFvISoIbF2g25x8N6VotQqrHzanvNK48H8RFQR/f38sLS2ZNWuWQe8bGxtLp06d6Nmzp36EV9OmTencuTPjx483aFmnT5+mfv361K9fH4CPPvqI+vXrM3HiRIOWYyxSwyEKpX5NKrLu7C02n7/DhG4+lLLJuW+CEMXOnQtw8OGXYpdvoFT+O3se//s+N2NTKGVtQRdfDwMHWDStWrWKDz74wODNFq6uroSGhmbbv3Xr1jzf49HaRk8SEBCQrXazKJEaDlEoNfJyoaqbPakZGjacM1FPeCEKWma6blSKNhNq94C6fZ7qNitO6GoGe9TzxM6q5P6u1Gq13L17l2nTpnH16lUmTZpk6pBKNEk4RKGkUqkY0FQ3RPO3YzeKdFYvRJ4dnAV3g8GuNHSdne+mFIB7CWnsvBgFwGvNSvYw54MHD1KuXDl+++031q1bh6Ojo6lDKtEk4RCFVp+GFbCxNOPy3URO34gzdThCGNftQF3fDYCu34LD0y2ytupUBJlahYZeLtQuV7K/YAMCAtBqtYSEhNC0aVNTh1PiScIhCi0nW0t6+utm6fvtuGHWOxCiUMpUw/ohoGigTm/d42luo9Gy8mFH69dLeO2GKHwk4RCF2qMq4e1BUdxPyn0lUyGKtP0zIPoS2LtBl2+f+jZ7Q+9xJz4NV3srOktnUVHISMIhCjXfCk74V3AiXaNlzelbpg5HCMOLPKObURR0/TbsSz/1rX478WgZ+gpYW5gbIDghDEcSDlHoParlWHHiBhpZtl4UJxlpD5tStLrJvXx6PPWtwmOSOXglGpUKBjQxTnOKVqs1yn2FaRT0v2fJHS8liozu/p5M2XqJW3GpHLwSTdtaZU0dkhCGsX8axFwG+7LQeeYz3er3h3032tRwo1JpAy5DD1hZWWFmZsbt27dxc3PDyspKlhwowhRFIT09nejoaMzMzLCyKphFMiXhEIWejaU5LzWswJLDYfx2/IYkHKJ4iDgFR+frtrvPBbunW6EUIC1Dwx+ndTOLvtbU8LUbZmZmeHt7c+fOHW7flnlxigs7OzsqVaqU67oyhiYJhygSBjStxJLDYey9fI+I2BQquhr2F5wQBSojVTfBl6IFv35Qq+sz3W5b0B3iUjIo72xrtITcysqKSpUqkZmZiUajMUoZouCYm5tjYWFRoDVVknCIIqGKmwMtq5Xh8LUYVp68yaedapk6JCGe3t4pcP8qOHhA5xnPfLvlD4eNv9q0EuZmxvsCUalUWFpaYmkpSw2I/JNOo6LIeK2ZbhGqNacjSM+UzmuiiLp5Ao4t0G33mKdboO0ZXLwdT+DNB1iaq+jbqGQvQy8KN0k4RJHRvrY77o7WxCSlsy3ojqnDESL/0lN0TSkoUG8A1Oj4zLf831Fd7UbHOh64lbJ+5vsJYSyScIgiw8LcTN8h7tcjYbK+iih69n4FsdehlCd0nPbMt4tNTmfDuUgABrao/Mz3E8KYJOEQRcqrTSthZWHG+VvxBEY8MHU4QuRd+BE4/qNuu8d8sHV+5luuPHkTdaYW3/JONPR6tqYZIYxNEg5RpJR2sKanvycAvx4JN20wQuRVejJsHAooUP91qN7+mW+ZodGy/JiuOWXQc5VlXgxR6EnCIYqcgc9VBmB70B2i4tNMG4wQebH7C4gLB8cK0HGqQW65IziKqIQ0yjhY09WvnEHuKYQxScIhipw6nk408XYlU6uw/Hi4qcMR4vHCDsHJn3XbPeeDjZNBbvvrkTBAN0eNrJsiigJJOESR9NbDWo7fT9wkLUMmIRKFlDrpYVMK0HAQVG1nkNuej3jA2YdDYQc8HC4uRGEnCYcoktrXdqe8sy1xKRlsOidTLYtCatdEeHATnCpBh68MdtulR8MB6ObnSdlSNga7rxDGJAmHKJIszM14o7luiOwvMkRWFEbX98HpJbrtnvPBupRBbnsvIY0tF3RJ9qCHNX1CFAWScIgiq1/jSthamhMalcjxv2NNHY4Q/0hLgE0f6rYbvwNVAgx2699O3CRDo9DQywW/Cs4Gu68QxiYJhyiynOws6d2gPPBPBzohCoVdEyA+Apy9oP0XBrutOlPD7yd0Q2Floi9R1EjCIYq0QQ8/dHdduktEbIppgxEC4NoeOLNUt93rB7B2MNitN5+/Q0xSOh6ONnSq62Gw+wpRECThEEVadfdStKpeBkWBJYellkOYWFr8P00pTd6Hyi0NdmtFUVh86G8AXm/uhaW5fHyLokX+x4oi791WVQBYfSqCBynpJo5GlGg7x0NCJLh4Q/tJBr31wasxhEYlYmdlrl9TSIiiRBIOUeS1ql6G2uUcSc3Q8NvxG6YOR5RUV/6CwN8Ala4pxcreoLdfePA6AK80roiTnaVB7y1EQZCEQxR5KpWK91p7A7D06A2ZCEwUvNQ42Dxct91sKHi1MOjtgyPjOXLtPuZmKt5u6W3QewtRUCThEMVCNz9PPJ1siElSsz4w0tThiJJmx3hIvAOuVaHd5wa//cKDur4bXX3LUcHFzuD3F6IgSMIhigVLczPeevjLb9Ghv9FqZSIwUUAub4fzv6NrSvkRrAybENyKS2Fr0B0A3mtdxaD3FqIgScIhio1+TSpRysaCv6OT2RN6z9ThiJIgJRY2j9Btt/gAKjU1eBG/HA5Ho1V4rlpp6pY3zMJvQpiCJByi2HCwtmDAw977jzrYCWFU28dA0l0oUwPafmbw28enZLDq1E0A3mtd1eD3F6IgScIhipVBz1XG0lzFqfA4zt6MM3U4oji7tAWC1oDKTNeUYmlr8CJ+O3GDlHQNtTxK0bp6GYPfX4iCJAmHKFbcHW3oWU833fnCA3+bOBrjiImJwdvbm/Dw8Dyd36NHD1Qqlf7Rvn17/bEDBw5Qu3ZtypQpw+zZs40UcTGUfB+2jNRttxgOFRoZvAh1pka/Kuy7raqgUqkMXoYQBUkSDlHsPOpYtzMkirCYZBNHY1gxMTF069Ytz8kGwOnTpwkKCiIuLo64uDg2btwIQHR0ND169KB///4cO3aMFStWsG/fPiNFXsxsHw3J0eBWCwLGGaWIDYGRRCeq8XC0obu/p1HKEKIgScIhip0a7qVoV6ssigI/HyhefTn69evHq6++mufzIyMjURSFunXr4uzsjLOzM/b2ugmpVqxYgaenJxMmTKB69epMnDiRJUuWGCv04uPiBgheBypz3QRfljYGL0KjVfjpYQ3dWy0rY2UhH9Wi6JP/xaJYGtZW18Fu3dlbRD5INXE0hrNo0SKGDx+e5/NPnjyJRqOhQoUK2Nvb069fP+LidH1bzp8/T9u2bfVV9U2aNOHMmTO53kutVpOQkJDlUeIkx8DWj3XbLUdB+YZGKWZr0B3CYpJxtrPkVZnGXBQTknCIYqmhlyvNq5QmQ6OwsBjVcnh752+WydDQUPz9/dm6dSvHjx8nLCyMceN0TQAJCQlZ7ufo6Mjt27dzvdf06dNxcnLSPypWrPh0L6Io2/oxpMRAWR9o86lRitBqFRbsvQbAW89542BtYZRyhChoknCIYuvDdtUAWHkqgnuJaSaOxjTGjRvHrl278Pf3x9fXl1mzZrF27VoALCwssLa21p9rY2NDSkrKY+8VHx+vf0RERBg9/kIl+E8I2fCwKeVHsLB+4iVPY9elu1y+m0gpawvebFHZKGUIYQqScIhiq3nV0jSo5Ex6ppbFh2TpeoCyZcty//591Go1rq6uREdH648lJiZiZWWV67XW1tY4OjpmeZQYSff+aUpp/Ql41jNKMYqi8P3D2o03WnjhZCuLtIniQxIOUWypVCo+bFcdgN+O3yAuueQtXf/KK69w+PBh/fNjx47h7u6OtbU1jRs35tixY/pjgYGBlC9f3hRhFm6KAltGQWosuPtCq0+MVtTBqzEERcZja2nOW8/JIm2ieJGEQxRrATXdqOPpSEq6hl+PFN9ajoSEBDIyMrLt9/X1ZdSoURw+fJgNGzYwbtw4hgwZAujm5zhy5Ai7d+8mIyODmTNn0rFjx4IOvfALXgehW8DMQjcqxSL3WqBnoSgK8/dcBWBA00qUdjBOk40QpiIJhyjWVCoVH7TV9eX49Wg4CWnZv5SLAz8/P7Zu3Zpt/5gxY/Dz86NTp04MGTKEoUOH8tlnuim4y5Qpw5w5c+jSpQvu7u5cvnyZzz83/EqnRVpi1L+aUj6Fcn5GK+pEWCynb8RhZW7Gu7JImyiGVIqiyLKaoljTahU6zD3ItXtJjO5Yk2EPExChExYWRmhoKK1atcLBwSHP1yUkJODk5ER8fHzx7M+hKLCyP1zZDh5+8O5eMDden4rXFp/g8LUYXmtWiSm9fI1WjhCmIjUcotgzM/unlmPxob9JSc80cUSFi7e3N507d85XslEiXFitSzbMLKH3T0ZNNgJvxnH4WgwWZirel0XaRDElCYcoEbr5lcOrtB1xKRn8dvyGqcMRhV3CHdj+cJ6NgLHgXseoxc172Hejd/3yVHS1M2pZQpiKJByiRLAwN9PXcvx04G+S1FLLIXKhKLB5BKTFg2d9eG6kUYs7cyOOfZejMTdTSXOfKNYk4RAlRu/65alSxp7Y5HSWFuMRK+IZnfsdru4EcyvdBF/mxp3pc/auywC81KAClcvYG7UsIUxJEg5RYliYmzGivW5ejoUH/yY+tXiOWBHPID4SdozVbbcdD2VrG7W4Y9fvc+TafSzNVXz4vNRuiOJNEg5RonTz86SGuwMJaZksOfS3qcMRhYmiwObhoE6A8o2g+YdGLk7R1270a1yJCi7Sd0MUb5JwiBLF3EzFqPY1AFhyOIzYEjj7qMhF4HK4thvMrQukKeXg1RhOhcdhZWEmfTdEiSAJhyhxOtbxoI6nI8npGn4+WHxWkhXP4EEE7Biv2273ObjVMGpxiqIw+y9d7cbrzbzwcLIxanlCFAaScIgSx8xMxUcv6L5Qlh0NL7EryYqHFAU2fQDpiVChCTQfZvQid1+6x/lbujVThgTIvBuiZJCEQ5RI7WqVpV5FZ9IytPy4X2o5SrQzv8Lf+8HCRteUYmZu1OK0WoXZu64AMPC5ypSRNVNECSEJhyiRVCoVH3fQ1XKsOH6TO/GpJo5ImERcOOx8uH7M85OgjPH7UmwPjuLSnQQcrC14r5WsmSJKDkk4RInVsloZmni7kq7RMnfXVVOHIwqaVgsbP4CMZKjUApoONnqRGRot3z4cmfJWS29c7I2z8qwQhZEkHKLEUqlUjOlUE4A/zkRw5W6iiSMSBer0Egg/BJZ20PN7MDP+x+GqUxH8HZ2Mq70V77TyNnp5QhQmknCIEq2hlyud6nigVWDG9lBThyMKSmwY7Jqo224/GUobv+NmkjqT73br+m6MeL46jjbGWwxOiMJIEg5R4n3aqSYWZir2ht7j6PUYU4cjjE2rhY3DICMFvFpC43cLpNiFB/8mJimdyqXt6N+kUoGUKURhIgmHKPGquDnwalPdF8D0baFotYqJIxJGdXIh3DgClvYF1pRyNyGNRQd1M9uO6VQLKwv56BUlj/yvFwIY/nx17K3MCYqMZ/OF26YORxjL/euwe7Ju+4UvwLVg+lHM3X2F1AwN9Ss506muR4GUKURhIwmHEEAZB2sGt9G148/aeRl1psbEEQmD02pgw1DITAXv1tDo7QIp9urdRFafigDgsy61UalUBVKuEIWNJBxCPPROqyq4O1pzKy6V5cdumDocYWgnfoKI42DlAD0KpikF4OsdoWgV6FjHnUaVXQukTCEKI0k4hHjI1spcP+X5/L3XiE+R5euLjZirsOdL3XaHKeDiVSDFHv/7Prsv3cPcTMWnnWoVSJlCFFaScAjxLy81rEgNdwfiUzOYt1cmAysW9E0paVClLTQcWCDFarQKU7deAqB/k4pUdXMokHKFKKwk4RDiX8zNVIzvUhvQLex27Z5MBlbkHVsAt06CVSnoMR8KqA/FH6cjCIqMp5S1BSOeN+7qs0IUBZJwCPEfATXL0r52WTK1Cl9sDkFRZJhskRV9GfZO0W13mgbOFQuk2PjUDGbu1E1hPqJ9ddxKyQJtQkjCIUQOJnTzwcrcjENXY9gVctfU4YinocmEDUNAo4Zq7aH+6wVW9NzdV4hNTqdaWQfebFG5wMoVojCThEOIHHiVtufd1ro5Gr7aGkJahgyTLXKOzoPIM2DtBN3nFVhTyuWoRP73cJTTpO4+WJrLx6wQIAmHELkaGlAND0cbImJT9bNEiiLi3iXYP1233Wk6OJUvkGIVReGLzRfRaBU61nGnVXW3AilXiKJAEg4hcmFvbcH4rroOpAv2X+P2g1QTRyTyRJMB6weDJh2qd4R6rxZY0TuCozh6/T7WFmZ83tWnwMoVoiiQhEOIx+juV44mlV1Jy9AyddslU4cj8uLIXLhzDmycoPt3BdaUkpquYcrDYbDvt6lKRVe7AilXiKJCEg4hHkOlUjG5Rx3MVLD1wh2OXb9v6pDE40QFw/6vddudZ4FjuQIr+qcD14l8kEp5Z1uGtDH+cvdCFDWScAjxBD6ejgxoqpuZ8vMNQbLOSmGlydCNStFmQM0u4Ne3wIq+Hp3Ej/uvAzC+S21srcwLrGwhigpJOITIg0861KSMgzXXo5P1XyyikDk0G6IugK0LdJtbYE0piqIw/s8g0jVa2tRwo4uvrAYrRE4k4RAiD5zsLJncQ9cJ8Id917l2L8nEEYks7lyAgzN1212+gVLuBVb0H6dvcSIsFltLc6b0qiurwQqRC0k4hMijrr7laFvTjXSNlvF/BqHVygykhUJm+sOmlEyo3R3q9imwomOS1PrOxKNeqC4dRYV4DEk4hMgjlUrFV73qYmtpzsnwWNacjjB1SALg4Cy4Gwx2paHrnAJrSgH4aksI8akZ+JRz5K3nvAusXCGKIkk4hMiHCi52fNxBtxDXtG2XuJeYZuKISrjbgXDoW912l2/AwbgTbWm0Cseu32fjuUh+3H+djeduY6aCGX18sZAZRYV4LPkLESKfBraojG95JxLSMvlyc0iBlh0TE4O3tzfh4eF5On/hwoWUK1cOS0tL2rRpw507d/THevTogUql0j/at29vpKiNJFOtW3Ze0YBPL6j7olGL2xF8h5Zf76X/ouOMWHWOr3eEAtC2Zln8KjgbtWwhigNJOITIJwtzM6a/6Iu5mYotF+6wN7RgFneLiYmhW7dueU42Dh8+zIQJE1i+fDlhYWEoisInn3yiP3769GmCgoKIi4sjLi6OjRs3GilyIznwNdwLAbsy0PVboxa1I/gOQ347y5347DVae0LvsSP4Tg5XCSH+TRIOIZ5C3fJOvPVcZQDG/RlEfEqG0cvs168fr76a92m6r169ys8//0z79u2pUKECgwYNIjAwEIDIyEgURaFu3bo4Ozvj7OyMvb29sUI3vMgzcHiObrvbbLAvY7SiNFqFLzaHkFsXYRXwxeYQNNKJWIjHkoRDiKf00Qs1qVLGnrsJaiZuCjZ6eYsWLWL48OF5Pn/QoEH06tVL//zy5ctUr14dgJMnT6LRaKhQoQL29vb069ePuLi4x95PrVaTkJCQ5WESGWmwfggoWqj7Evj0NGpxJ8Nic6zZeEQB7sSncTIs1qhxCFHUScIhxFOytTLn277+mKlg47nbbL1g3Gp1b++nHwURGxvLzz//zODBgwEIDQ3F39+frVu3cvz4ccLCwhg3btxj7zF9+nScnJz0j4oVKz51PM9k/3SIuQz2ZaHLLKMX9++Owdr0NG583Y0bX3dDm56W63lCiOxUiqJIPaAQz+CbnZf5ft81XOws2TmqNWVL2Ri1PJVKRVhYGJUrV87zNf379ychIYGtW7fmePzgwYO8+OKLxMTE5HoPtVqNWq3WP09ISKBixYrEx8fj6OiY51ieScQp+KWDrnaj3+9Qq6vRizx2/T79Fx0HdAlHxJyXAKg4ai1mVjZEb5pFetQ1alRyx1ybQWJiov4xYsQIZs6cafQYhSgKLEwdgBBF3fDnq7M39B4hdxIYty6IxW82KlSzTS5btox9+/Zx/vz5XM8pW7Ys9+/fR61WY21tneM51tbWuR4rEBmpugm+FC34vVIgyQZAE29X3B2tuZugzvF45oM7ZMZFEhp/hzp16tChQwcqV65MqVKleOGFFwokRiGKAmlSEeIZWVmYMeeVeliZm7En9B5/nL5l6pD0Tp8+zYcffsiqVatwd/9nuu9XXnmFw4cP658fO3YMd3d30yYUT7JvKty/Cg7u0GlGgRVrbqaicumcO9SqAI/+06lS0wcHBwciIyNZuHAhR44coVatWtSoUaPA4hSisJOEQwgDqOlRSj8h2BebLxIRm1JgZSckJJCRkX2UzL179+jevTuffvopjRo1IikpiaQk3Rowvr6+jBo1isOHD7NhwwbGjRvHkCFDCizmfLt5Ao5+r9vu/h3YuRZY0duD7nAiLBaVClztLbMc83Cy4edBzTm0dxcODg5UrVqVhQsXEhERwQsvvICvry+LFy8mNTW1wOIVorCShEMIA3mnVRUaV3YhOV3DR2vOkanRFki5fn5+OfbNWLlyJVFRUUyYMIFSpUrpHwBjxozBz8+PTp06MWTIEIYOHcpnn31WIPHmW3qKrikFBfz7Q83OBVb0nfhUxq8PAmBoQFUOftpOf2zpoMYcHtOOTnXL4enpycaNGwkODmb//v0EBgayb98+qlWrxnvvvUfFihX5/PPPuX37doHFLkRhI51GhTCgm/dT6DrvEInqTIYGVOXTTrVMHZLRJCQk4OTkZPxOozvGwfEfoFQ5GHocbJ2NV9a/ZGq09F90nFPhcdQt78ifQ54jQ52Kg4MDAElJSdnmLlmzZg2vvPIKq1evpm/fvgBcv36defPm8csvv5CWlsYrr7zCqFGjaNiwYYG8DiEKC6nhEMKAKpW2Y0YfPwB+2H+dA1eiTRxREXfjKBz/UbfdfV6BJRsAs3dd4VR4HKWsLVjwagOsLMwwNzenS5cudOnSBXNz82zX9O3bl23btvHcc8/p91WtWpXvvvuOW7duMXPmTI4cOUKjRo1o1aoV69atIzMzs8BekxCmJDUcQhjB5xuC+O34TVztrdg2vBUeTsYdKmsKRq/hSE+GH5+DuDCo/xr0XGD4MnJx4Eo0b/5yEoAFrzagq185g91bo9GwadMm5s6dy8GDB/Hy8uLDDz/k7bffxtnZ2WDlCFHYSA2HEEbweVcffMo5EpuczvBVgQXWn6NY2f2FLtlwLA8dpxVYsVHxaYxafQ6A15pVMmiyAWBubk7v3r05cOAAZ86coU2bNowbN44KFSrw4YcfcvXqVYOWJ0RhIQmHEEZgY2nOggENsLcy52RYLN/tkS+RfAk7BCd/1m33mA82TgVSbKZGy/BVgcQmp+NTzpHPu/oYtbwGDRqwbNkybty4wccff8zq1aupWbMm3bt3Z+/evUgFtChOJOEQwki8y9gz/WF/ju/3XePQVenPkSfqJNg4VLfdcCBUe77Aiv5uz1VOhsVib6VLGG0ss/bTSE5Oxt7eHnt7e5KTkw1Wbrly5fjiiy+4efMmixcv5saNGzz//PP4+/vrO5sKUdRJwiGEEfXw96R/k0ooCgxfGcjN+wU3P0eRtWsiPLgJThXhha8KrNgdwVHM33sNgOl9/PAuk/NkXykpKaSkGOff0cbGhrfeeovz58+zZ88evLy8eOedd6hUqRITJ07kzh3jrtcjhDFJwiGEkU3q7oNfBSfiUjJ493+nSVLLqIRc/b0fTi/RbfeYDzYFs0ZLaFQCH605B8Cbzb3o4e9ZIOXmRqVS0a5dOzZv3szly5fp168fs2fPxsvLizfeeIOzZ8+aND4hnoYkHEIYmY2lOQtfb0TZUtZcvpvIqNXn0GqlbT6btATY+IFuu9HbULVtgRR7P0nNO8tOk5Ku4blqpZnQzbj9NvKrevXqzJs3j1u3bjFjxgwOHjxIw4YNadOmDevXr0ej0Zg6RCHyRBIOIQqAh5MNP7/eECsLM3aF3GX2riumDqnw2TUB4iPA2Qte+LJAikzP1DJkxVluxaXiVdqOBa82wMK8cH4sOjs789FHH3Ht2jXWrl2LVqvlxRdfpFq1asyZM4f4+HhThyjEYxXOvywhiqH6lVz4uo8voOtEuum8THOtd20PnFmq2+65AKwdjF6koihM3nyRk2GxOFhbsPiNRjjbWRm93GdlYWFBnz59OHToEKdOnaJly5Z8+umnVKhQgREjRnDt2jVThyhEjiThEKIA9a5fgffbVAFg9B/nCbolv0pJi4dNw3XbTd4H71YFUuxvx2/w+4mbqFQwr389qruXKpByDalRo0YsX76cGzduMHLkSH7//Xdq1KhBz5492bdvnwyrFYWKJBxCFLBPO9aiXa2yqDO1vLXsVIGuLFso7fwMEm6Bize0n1QgRe4OucvkzSEAjOlUi3a13PN0nZmZGW3atKFNmzaYmRWej09PT0+++uorbt68ycKFC7l+/Trt2rWjXr16/PrrrzKsVhQKMrW5ECaQmJbByz8dIzQqkcql7Vg7pAVlHKxNHVa+GGRq86u7YUUfQAWDtoFXC4PGmJNT4bG8tvgE6kwtLzWswKyX/FCpVEYvtyApisKePXuYO3cuW7dupWzZsgwZMoTBgwfj4eFh6vBECVV4UnQhSpBSNpb8760mVHCxJfx+CgN/PUliWoapwypYqQ9g04e67WZDCiTZCI1K4O2lp1Bnanm+VllmvOhb7JIN0A2rbd++PVu2bOHy5cu8/PLLzJo1Cy8vLwYOHMi5c+dMHaIogSThEMJEyjrasPztppS2tyI4MoH3/neGtIwSNMRx53hIvA2uVaHdBKMXFxGbwhtLTpKQlkkjLxe+L8QjUgypRo0afP/999y6dYupU6eyb98+6tevT0BAAFu2bDF1eKIEKf5/bUIUYt5l7Fk6qAn2VuYc+/s+o1afQ1MS5ui4shPOrQBU0OtHsLIzanExSWre+OUk9xLV1HQvxZI3G2NrlX15+SdJTk7Gzc0NNzc3g05tXhBcXFz45JNPuH79OmvWrCEjI4MePXpw//59U4cmSgjpwyFEIXD0WgwDfz1FukZLv8YVmdbbFzOzwl3V/9R9OFLjYEEzSIqC5h9Ax6nGCxKIT8lgwJLjBEcmUN7ZlnVDWuDhZPNU90pOTsbBQTdkNykpCXv7nKc/LyqSkpL0r0cIY5MaDvHUunTpwsSJE3nuueeoUqUKwcHBpg6pyGpRrQxz+9VDpYJVpyIY++eF4lvTsX2sLtkoXR3afW7UouKS03l1sS7ZcLW3YvnbTZ462SiOJNkQBUkSDvHUgoODqVSpEkeOHGH48OFs3LjR1CEVaV18yzG7rz9mKlhz+haf/HGeTI3W1GEZVug2uLAKVGa6phRLW6MVFZOkpv+i41y8nUBpeyt+f7cpVdzkC1YIU5GEQzyVhIQEVCoV77zzDgAZGRk4OzubNqhioHf9CszrXx9zMxXrAyMZsfocGcUl6UiJhS0jddsthkPFxkYr6l5CGv0WHic0KhG3Utaseq8ZtTwKZiE4IUTOJOEQTyU4OJjGjf/5wggKCqJOnTomjKj46ObnyQ8DGmBprmLrhTt88PtZ0jOLQdKx/VNIugtutSBgnNGKuROfyisLj3PtXhLlnGxY837zIjmLqBDFjSQc4qkEBwfj7++vfx4UFISvr68JIypeOtbxYOHrjbCyMGPnxbu8t7yIL2sfsgmC/tA1pfT8ASyN04/i7+gkXvn5OGExyZR3tmXN+83xLlO0O3YKUVxIwiGeSnBwMH5+fgBkZmby4MEDSpcubeKoipe2tcqy5M1G2Fiasf9yNC//dIw78ammDiv/kmNgyyjddstRUKGhUYo5/vd9ev9wlJuxKXiVtmPN4OZUdDXscFszMzMaNWpEo0aNCtXU5sYWERFBQEAAPj4++Pn58ccff5g6JFEEybBYIQq5cxEPeGfZaWKS1JQtZc2SNxvjW8HJ1GHlfVjsHwPh4noo6wPv7QcLw0/h/sfpCMavDyJDo1C/kjMLX2+EW6miNVV8YXbnzh3u3r1LvXr1iIqKomHDhly5cqXIDwsWBavkpOhCFFH1KjqzYVgLarqX4l6imr4/H2PnxShTh5U3wX/qkg2VuW5UioGTDa1WYdbOUEavvUCGRqGbXzlWvttMkg0DK1euHPXq1QPAw8ODMmXKEBsba9qgRJEjCYfIk2+++QaVSpXnx+DBg00dcrFSwcWOtUOa06aGG6kZGgb/doafDlwv3MuPJ92DrR/rtlt9DJ71DHr7ZHUmH64MZMG+6wB82K4a8/rVx8Yy/zOICliwYAGVK1fGxsaGpk2bcvLkyRzPO3PmDBqNhooVKxq0/IMHD9K9e3c8PT1RqVRs2LDBoPfPj7y+FyJ/SnTCsXfvXr799ltTh1Ek/LvqtHTp0lStWvWxj7Jly+a7jMLSTlxY4vivUjaWLHmzEa8380JRYMb2UN5aeor7SWpTh5adosDWjyA1FtzrQuvRBr19cGQ83ecfZmvQHSzNVXz7sj8fd6hp9NlZU1JSqFy5MpUrVyYlJcWoZRWk1atX89FHHzFp0iTOnj2Lv78/HTt25N69e1nOi42N5Y033mDhwoV5um9AQABLly7N07nJycn4+/uzYMGC/IZvUHl9L8RTUITIg4yMDKVnz54KoFSsWFG5ceOGwcu4ffu2EhgYqCiKoty5c0fx9PRUkpKSDF5OUYkjN1qtVll+LFyp/tk2xWvMFqXxlF3KkavRBR5HfHy8Aijx8fHZD174Q1EmOSrKF66Kcvu8wcrUarXKkkN/K9XH6157s2m7lZNh9w12/ydJSkpSAAUoVP8nnuT3339XbGxslNu3b+v3DRw4UPH19VUePHigNGnSRBk2bJj+mEajUTw9PZXp06fr96WlpSmtWrVS/ve//+W53DZt2ii//vprvuMFlPXr1+f7urwoX768smDBgiz7jhw5otja2irh4eF5ei/E0ynRNRw9evQgKCjI1GE8FUVRmD17Nt7e3tjZ2dGrVy/i4+ONVp6FhQWrV6+mffv2RERE0L59e+7evWvQMgqqnXjs2LF069bN5HE8LZVKxWvNvNj0wXNUK+vAvUQ1A5acYNbO0MIxSVjiXdj2iW679Wgo52eQ295PUvP2stN8uSWEdI2WF3zc2Ta8FY0ruxrk/sVZv379qFGjBtOmTQNg0qRJ7N69m+3bt2Nra8uZM2do3769/nwzMzPat2/PsWPHAN3nzcCBA2nXrh2vv/66SV7Dv02bNg0HB4fHPm7evJnjtU2bNuXUqVP654qiMHLkSEaNGkW5cuWe+F6Ip2dh6gBMKTQ0lFq1apk6jKcyevRoNm7cyLJly7C3t6dXr15MnjyZOXPmGK1Ma2trNmzYwAsvvMCxY8fo0KED+/fvx8XFxeBlGaudGODcuXM0bJi3oZnGjONZ1fJwZPMHLflyy0VWnoxgwb7rHL52n+m9ffHxNNGsmoqiGwKbGgcefrq+G898S4WdF6OYuPEi9xLVWFmYMaFrbV5r5oVKVbgXuCssVCoVU6dO5aWXXsLDw4P58+dz6NAhypcvz+3bt9FoNLi7u2e5xt3dndDQUACOHDnC6tWr8fPz0/etWL58ucnm3hk8eDB9+/Z97Dmenp457m/WrBnLli3TP1++fDkRERGMGzeOmJiYJ74X4hmYtoIl/562iu6/EhISFF9f3wIt01DlHD9+XFGpVMqZM2f0+7744gulRo0aBivjceLi4hR/f38FUJo1a6YkJiY+0/3+6/79+4qPj49y5MiRPF+Tn9fl7u6urFq1yihxmMqW87eVupN2KF5jtihVxm1Vvth0UUlITTdqmTk2qZxb9bAppbSiRAU/cxnhMUnKm7+cULzGbFG8xmxRnv92vxJyO4cmnAJSVJtUHqlfv75iZWWl7N+/X78vMjJSAZSjR49mOXf06NFKkyZN8nX/qVOnKvb29vqHmZmZYm1tnWVfXppjMWKTysGDBxUzMzMlMTFRSUpKUsqXL68sXrxYURTDvhciuwJrUlm5ciW2trbcuXNHv2/QoEH4+fkZpSmgQoUK/PDDD1n2HT16FDs7O27cuMHFixeNMhX38ePHef755yldunS2kRsJCQkGKeObb77h+eefp0GDBvp97u7uxMTEGOT+T+Ls7Mxff/1FzZo1OX78OD179kStzlvHxUmTJuHr64u9vT3u7u4MGTKEjIwM/XG1Wk2vXr0YO3YsLVq0MHjsUVFR3L17F41GQ+vWrbGzs6Nx48bZmtaMHYehdfUrx1+jWtPVtxwarcIvR8J4/tsDbD5/u+BGsiTcge0PO4cGjAH3p//7SsvQMHf3FV6Yc5D9l6OxMjdjeLtqbPmwJbXLyZooT2PHjh2EhoZm+wVfpkwZzM3NszWR3r17Fw8Pj3yVMXjwYM6dO6d/NGrUiC+//DLLvtxqHvLjWZpUGjZsiJmZGWfPnuXrr7/Gzc2NQYMGAYZ9L0R2BZZwPK4N0cnJ8JMYPa6dzsvLyyhTcZ8/f56AgADq16/PoUOH2LFjB66urjz//POsXr368ZMj5ZFarWbr1q307t07y/60tDSjvI+5KVu2LLt27cLLy4u9e/fyyiuvkJn5+Km3FUVBURR+/vlnQkJCWLp0KevWrWPx4sX648ZuJz537hwAc+fOZfr06Zw+fRoHBwf69++fJc7C1F6dV+WcbFkwoAH/e6sJlUvbcS9RzYcrA3l10QlOhRu5D4qiwOYRkBYP5erBc6Oe6jaZGi3rA2/Rce5B5u6+SnqmllbVy7BjZCs+6lBThrw+pbNnz9K3b1+WLFnC888/z4QJE/THrKysaNiwIXv27NHv02q17Nmzh+bNm+erHFdXV6pVq6Z/2NraUrZs2Sz7LCyevSX/v4lNTo/cEhs7Ozt8fX1Zt24d33zzDXPmzNHPGmvI90LkoCCrUzZv3qxYW1srU6ZMUVxcXJTg4PxXuea16nzmzJlKnTp19M+XLVumeHh46Kv/P/zwQ2Xjxo0GLbN169ZK//79s+wbNmyY0qxZM4OVc/ToUQVQbGxsslRTWllZKR07djRIGflx9epVxd7eXgGU4cOH5/v6/v37KyNGjFAURVEOHTqkqFQqxd/fX/+4cOFCnu6T19c1ffp0xcbGRomMjNTvO3LkiAIo0dHRzxxHYZGanql8t/uKUuPhSBavMVuUvj8dVQ5fjVa0Wq1BysjSpBK4QteU8mUZRbkbku97qTM0yqqTN5TWM/fq420ydZey5fxtg8VrCMnJyYqPj4/i4+OjJCcnmzqcPAkLC1M8PDz0oyxyapJdtWqVYm1trSxdulQJCQlR3nvvPcXZ2VmJiop6prLz83mTmJioBAYGKoGBgQqgzJ49WwkMDDTKiLghQ4YoKpVK6dWrV7ZjxnovhO4XZ4HKqQ1RURRlz549yjfffJPt/KdtE3xcO92TPE2ZUVFRipmZmXLo0KEs+z/99FOlefPmBitn6dKlir29vXL16tUsjxo1aihffvmlwd6/vJoxY4YCKM7Ozk/8Ug4PD1eGDh2q1KlTR3F2dlbs7e0Vc3NzZdasWfku92lf1yuvvKK88cYbWfaFhIQogHL37t18x1HY3byfrIxdd0GpNn6r/ou894LDyq6LUUpGpuaZ7q1POG5eUpRpFXUJx6HZ+bpHYlqG8r+jYUqL6Xv08dX/8i/l+71XlcS0jGeKT+j6IdWsWVN5//33s+zv0qVLth8o8+fPVypVqqRYWVkpTZo0UY4fP/7M5ecn4di3b5++f8y/H2+++eYzx/FfP/30k2JlZaVcvXo1x+PGeC+EohToWio7duzgxRdfJD09neDg4DyNEImNjc0yJHHAgAH06dOHF198Ub+vcuXK2arpUlJScHJyYs+ePezevZvNmzdz5syZPC249DRlbtu2ja5du5KQkECpUv8shd2+fXt8fHyYN2+eQcqZP38+3377LeHh4fp9N27cwNvbm+DgYHx8fJ65jLxaunQpgwYNwsbGhr/++otWrVrlem50dDR16tShXbt2vPXWW5QvXx6NRkOjRo3YunUrL7zwAqCbjC0wMJCPP3786IanfV21atXi/fffZ9Sof6r8f/31VyZMmMCtW7fyFUNRcvtBKgsP/s3KkzdRP1zq3q2UNT39PXmxQYWnGtWiX0tlYXccIw9A+Ubw1k4wf/z/pUyNliPX7/Pn2VvsvBhFWoYunjIO1rzfugoDmlXCzqpED6ATRta2bVsaNGggEz8WsAL7q/53G+LSpUuZMGFClhkce/TowdSpU7P1q3B1dcXV9Z9x9v9uE3ycf7fTLVq0iG3btuV5dcenKVOr1X1oJicn6xOOCxcucPDgQaZMmWKwcsqUKUN8fDyKouiHBE6dOpUuXbpkSzaetoy82LJlC++++y7m5uasWrXqsckGwObNm9FoNKxcuVIf9/fff09GRoZ+zguAdu3a0a5duyeW/zSvKyUlhatXr6LRaPT7tFot3333HQMHDsx3DKYSExND48aN2bdvH5UrV37i+QcOHGDw4MFER0czYswEzOt0YO2ZW0Qnqll8OIzFh8PQxt2ic+0yDOnzPHU9HbEwz0f3rr/3g50N9Poh12QjWZ3J2ZtxHLgczcbzt4lO/KeTcZUy9rzZojKvNK4ofTSE0Wi1WqKjo1myZAlXr15l48aNpg6pxCmQhCM8PJyuXbsyfvx4+vfvT5UqVWjevDlnz57Vj7QwxpwYzZo1Y/78+fTs2ZOAgACD3vu/mjZtiq2tLaNHj+azzz7j+vXrDBs2jGHDhtGsWTODldOuXTvS0tKYMWMG/fr1Y8WKFWzevLlA5/o/evQoffv2JTMzk8WLF9OzZ88nXlO6dGkSEhLYtGkTPj4+bN68menTp1O+fHnc3Nz05+WWeBrChQsXMDc359dff6VNmzY4Ojry2WefkZqaypgxYwokhmcVExNDt27dstRwPU50dDQ9evTg448/pn///vTr149vvvHjk3HPs3zXacYv2ohDjebgUoGdUbBzwRHsrMxp6OVCU29XGni5UMnVDg9Hm+xJyINb/2y3+xzcagK6ESaRD1L5OzqZU+GxnAiLJTgyHo32n8pUFztLevh70rtBBfwrOBWZ+TRSUlJo3LgxAKdOncLOzs7EEYm8OnjwIO3ataNWrVqsW7fOIJ34Rf4YPeGIjY2lU6dO9OzZk7FjxwK6L+fOnTszfvx4duzYQWJiIjY2NlhaWhq0bH9/fywtLZk1a5ZB75sTNzc31qxZw8cff4yfnx+VKlXigw8+4KOPPjJoOe7u7ixdupTRo0fz1Vdf0a5dOw4fPlxgE1OFhITQrVs3UlNTmTZtGm+//XaeruvevTtvv/02r7/+Ora2trz22mv07duXGzduZDnPmJOxnTt3jho1ajBx4kR69+7NgwcP6N69O0ePHs3SDFaYJ4Tr168fr776KidOnMjT+StWrMDT05MJEyagUqmYOHEiS5YsoW3btgTt/J36KaGsnjiZrUF3WLztGLfUNqSkw6GrMRy6+s8wa3MzFR6O1niUssKtlDXmKAwM080mGm5Ti5/DmnHr3BEi41KJyWVtl/LOtjT1dqWzbzna1HDDyqLoTXSsKAohISH6bVF0BAQE6GuihWkUaB+O3Bw/fpzvvvuOlStXGvS+0k5nWBEREbRo0YJbt24xYsQI5s6da9D7JyYm8txzz3HhwgWD3reoxfA4YWFheHt7o1KpCAsLe2KTyqBBg7C1tdXPSXPnzh3atWvHpUuXaNu2LZ07d+bTTz8F4NixY3zx5ZfM+WU1J8NiORkWS1BkPHfiU8nQZP2Y6G++h3HaxTjNSKTlqHlEWFXJctzOypyKLnbUr+RM0yquNK7sSgWXol8bkJycjIODAwBJSUlZFjUUQjxeoeiZZcg5MaSdzjhiY2Pp2LEjt27don///kaZQt1Yk7EVtRgex9vbO1/nJyQkZOnb4+joyO3bt/XH/n0/R0dH7ty+Te1yjtQu58ibLSoDoNUq3EtUE3YvnhsxiaTfv0m/wJWkPVwstW+H1pQq5YiHky0VXGwp72yLs51lkWkmEUIUjEKTcPx7sZxnIe10xvH+++9z6dIlQDdr7JNqo2rWrJnvtQeMMRlbfhWGGAzJwsICa2tr/XMbGxv9suqPO/ZvZmYqPJxs8HCyoXlVN1g+CjQppFVoAuzhzRbe8ncmhHiiQpFw5DRk9GlJO51xWFlZUbVq1Tyf7+Xlle8yDJl4Pq3CEIMhubq6Eh0drX+emJiIlZXVE4/l6swvEHYQLGyh6zfwQX2jxC2EKH4KRcIhCr8VK1YYvQxDJp5FOQZDaty4Mb///rv+eWBgIOXLl9cfO3bsmL7j77+P5SguHP6aqNtuPxlcq+R+rhBC/EfR6yYuhMgmISEhyyJ4j/To0YMjR46we/duMjIymDlzJh07dgSgT58+rFq1iqCgIJKSkpg3b57+WDZaLWz8ADKSwes5aPKeMV9OoaVSqfDy8sLLy0v6qAiRT5JwiFzt3bv3qUb49O7dGxcXF1566SUjRCVy4ufnx9atW7PtL1OmDHPmzKFLly64u7tz+fJlPv/8c0A3bHzEiBE0atSI8uXLY25uztChQ3Mu4NRiCD8ElnbQ83vI4yR6xY2dnR3h4eGEh4fLHBxC5FOhGBYripf9+/eTmJjIsmXLWLt2ranDEeiG04aGhtKqVSv9sM5HQkJCiIyMpE2bNjn34bh/HX5qCRkp0OUbaPIu8K+pzePjpdOoEOKJSubPFJEnPXr0ICgoKN/XBQQEZJlIS5iet7c3nTt3zpZsAPj4+PDCCy/knGxotbBxmC7ZqNwKGuVtojchhPgv6TQqcvXfGTebNm2KWp19FsnNmzcX2EynooCd+AluHgMrB+i5oMQ2pTySmppK69atAd0QfFtbWxNHJETRIQmHyFFO083ndTptUUzEXIM9X+i2O3wFLvkf6lzcaLVaTp8+rd8WQuSdJBwiRznNuCk1HCWIVgMbh0JmGlQJgIaDTB2REKKIk4RD5CinGTelhqMEOf4DRJwAq1LQ43uQIaBCiGdUshtkRa6CgoKoW7fuU13bvn17Xn75ZbZt20aFChU4duyYgaMTRhV9BfZ8pdvuOBWcpfZKCPHsZFisEOIfmkz4pQNEnoGqz8Nr63Kt3SiJw2JltVghnp7UcAgh/nFsvi7ZsHaCHvOlKUUIYTDSh0MIoXMvFPZN0213mg5Oj1lXpQQrU6aMqUMQokiShEMIoWtK2TAYNOlQvSPUe9XUERVK9vb2WVbYFULknTSpCCHgyFy4HQg2TtD9O2lKEUIYnCQcQpR0dy/C/hm67U5fg2M508YjhCiWJOEQoiTTZMCGIaDNgJpdwL+fqSMq1FJTUwkICCAgIIDU1FRThyNEkSJ9OIQoyQ7PgTvnwdYFus2VppQn0Gq1HDhwQL8thMg7qeEQoqSKCoIDX+u2O8+CUu6mjUcIUaxJwiFESZSZ/rApJRNqdQPfl0wdkRCimJOEQ4iS6NC3uhoOW1foNkeaUoQQRicJhxAlze1zcOgb3XbXb8ChrEnDEUKUDJJwCFGSZKbDhqG6phSfnlDnRVNHJIQoIWSUihAlycGZcO8i2JWGLt9KU8pTsLOzM3UIQhRJknAIUVJEnoVDs3Xb3eaAg5tp4ymC7O3tSU5ONnUYQhRJ0qQiREmQqdaNSlE0umYUn56mjkgIUcJIwiFESbB/OkSHgr0bdPnG1NEIIUogSTiEKO5unYYj3+m2u80B+9KmjacIS0tLo2vXrnTt2pW0tDRThyNEkSJ9OIQozjLSHjalaMG3L9TubuqIijSNRsO2bdv020KIvJMaDiGKs31TIeYKOLhD569NHY0QogSThEOI4urmCTg6X7fd/TuwczVtPEKIEk0SDiGKo/QUXVMKCvj3h5qdTR2REKKEk4RDiOJo7xSIvQ6lykGn6aaORgghJOEQoti5cQyO/6Db7j4PbF1MG48QQiAJhxDFS3oybBwKKFD/NajRwdQRCSEEIMNihShe9nwJsX+DY3noOM3U0RQ79vb2KIpi6jCEKJKkhkOI4iL8MJz4SbfdYx7YOJk2HiGE+BdJOIQoDtRJumXnARq8CdXamzYeIYT4D0k4hCgOdk+GBzfAqSJ0mGLqaIqttLQ0Xn75ZV5++WWZ2lyIfJKEQ4giJDg4mMaNG+Pi4sLo0aN1/Qn+PgCnFulO6DEfbBz15w8cOBCVSpXtER4ejqIoODs7Z9k/ZYokK4+j0WhYu3Yta9eulanNhcgnSTiEKCLUajXdu3enYcOGnD59mpCQEH775SfY+IHuhEZvQdW2Wa754YcfiIuL0z+2bdtG9erVqVixIlevXsXZ2TnL8dGjR5vglQkhSgIZpSJEEbF9+3bi4+OZPXs2dnZ2TJs2jbD5vaBCLDhXghe+zHaNnZ0ddnZ2+udz5sxh8uTJmJubc+rUKZo3b46zs3PBvQghRIklNRxCFBHnz5+nWbNm+gTCz/4+vSrE6g72XADWpR57/alTpwgLC6Nfv34AnDx5kpMnT+Ls7EzZsmX5/PPPHzvkU61Wk5CQkOUhhBB5JQmHEEVEQkIC3t7euidpCag2fajb9HsDvFs/8fr58+czZMgQzMx0f/ZXrlyhe/fuBAYG8vvvv/PTTz+xevXqXK+fPn06Tk5O+kfFihWf/UUJIUoMlSKz2AhRJIwZM4aMjAxmz54Nmz6Es//jRoIKy+En8axc47HXxsbG4u3tTXh4OC4uOU91/uWXX3LhwgXWrl2b43G1Wo1ardY/T0hIoGLFisTHx+Po6JjjNcVNcnIyDg4OACQlJWFvb2/iiIQoOqSGQ4giwtXVlejoaLi2G87+D4AhOxUs7Z+8Vsqff/5Jq1atck02AMqWLUtkZGSux62trXF0dMzyEEKIvJKEQ4gionHjxgSfPgIbdU0p8bX7s+/vdFxdXZ947Zo1a3jxxRf1z1NTU/H19SU1NVW/79ixY3h5eRk+8GLEzs6OpKQkkpKSsnTGFUI8mYxSEaKIaN26NaP94iBRC65VGL9HTfv27TE3N+fBgweUKlUKc3PzbNelpqZy4MABfvrpJ/0+W1tb3N3dGTp0KMOGDePQoUP8/vvv7N69uyBfUpGjUqmkGUWIpyQJhxBFhMXfe3i1thatotB90Q1O3Y1k//79ALi4uBAYGEi9evWyXXf06FFcXFyoUqVKlv2//PILAwcOpGXLllSuXJlVq1bRpk2bAnglQoiSSDqNClEUpMbBgmaQFEWy3yD2W79As2bNKF26tMlCSkhIwMnJqUR1GlWr1bz//vsA/Pzzz1hbW5s4IiGKDkk4hCgK1g+G8yuhdDUYfBgsbU0dUYlMOGSUihBPTzqNClHYhW7TJRsqM+j1U6FINoQQIr8k4RCiMEuJhS0jddvNP4CKjU0ajhBCPC1JOIQozLZ/Ckl3oUwNaPuZqaMRQoinJgmHEIXVpc0Q9Me/mlJsTB2REEI8NUk4hCiMku/DllG67edGQoWGJg1HCCGelSQcQhRG2z6B5Ghwqw0BY00djRBCPDOZ+EuIwubierj4J6jMofePYCFzPRQWdnZ23Lt3T78thMg7STiEKEySomHrx7rtVh+BZ33TxiOyUKlUuLm5mToMIYokaVIRorBQFNj6EaTcB/e60PpTU0ckhBAGIwmHEIXFxT/h0iYws4BeP4CFlakjEv+hVqsZNmwYw4YNQ61WmzocIYoUmdpciMIg8S780FS3ZkqbsdB2nKkjeiKZ2lymNhciP6SGQwhTUxTdENjUOPDwhdafmDoiIYQwOEk4hDC1oD/g8lYws4ReP4K5pakjEkIIg5OEQwhTSoyCbaN1223G6Go4hBCiGJKEQwhTURTYPBLSHkA5f2g50sQBCSGE8UjCIYSpnF8FV7Y/bEr5SZpShBDFmiQcQphCwm3YMUa33XYcuPuYNh4hhDAymWlUiIKmKLB5BKTFg2cDaDHC1BGJPLK1tSUsLEy/LYTIO0k4hCho51bA1b/A3OrhqBT5MywqzMzMqFy5sqnDEKJIkiYVIQpS/C3Y8XBSr7afQdlapo1HCCEKiCQcQhQURYFNw0GdABUaQ4sPTR2RyKf09HRGjx7N6NGjSU9PN3U4QhQpMrW5EAXlzDLYPBwsbGDwYShT3dQRPROZ2lymNhciP6SGQ4iC8OAm7PxMt91uQpFPNoQQIr8k4RDC2BQFNn4A6YlQsRk0G2LqiIQQosBJwiGEsZ3+BcIOgIUt9FwAZuamjkgIIQqcJBxCGFNcOPw1Qbf9/EQoU82k4QghhKlIwiGEsWi1uqaUjGSo1AKaDjZ1REIIYTKScAhhLKeXQPghsLSDXgvATP7chBAll0xxKIQxxP4Nuybqttt/Aa5VTBuPMAhbW1uCg4P120KIvJOEQwhD02phwzDISIHKraDxO6aOSBiImZkZderUMXUYQhRJUscrhKGd/BluHgVLe+j5vTSlCCEEUsMhhGHdvw67v9Btd/gKXCqbNBxhWOnp6UybNg2A8ePHY2VlZeKIhCg6ZGpzIQxFq4Ffu0DEcfBuA29sBJXK1FEZjUxtLlObC5EfUtcrhKEc/1GXbFiV0jWlFONkQwgh8ksSDiEMIeYq7P1Kt91xCjhXMkoxwcHBNG7cGBcXF0aPHk1eKij9/PxQqVT6xzvv/NOJde3atXh5eeHp6cnKlSuNErMQQoAkHEI8O60GNgyBzDSo2g4avGmUYtRqNd27d6dhw4acPn2akJAQli5d+thrUlJSuH79Ovfu3SMuLo64uDjmz58P6JKXAQMGMGHCBHbu3MnEiRO5fPmyUWIXQghJOIR4Vse+h1unwNoResw3WlPK9u3biY+PZ/bs2VStWpVp06axZMmSx14TGBiIn58fbm5uODs74+zsrJ8/YvHixbRt25Z33nkHX19fPvjgA5YvX26U2IUQQhIOIZ5F9GXYO1W33XEaOFUwWlHnz5+nWbNm2NnZAbqmkpCQkMdec/LkSW7duqVPOIYMGYJardbfr127dvpzmzRpwpkzZ3K9l1qtJiEhIctDCCHyShIOIZ6WJlPXlKJRQ7UXoP5rRi0uISEBb29v/XOVSoW5uTlxcXG5XnP58mVatmzJ4cOH2blzJ7t27WLOnDk53s/R0ZHbt2/neq/p06fj5OSkf1SsWNEAr0oIUVJIwiHE0zo6DyLPgLUT9Jhn9FEpFhYWWFtbZ9lnY2NDSkpKrtf89NNPrFy5kpo1a9K0aVMmTpzI2rVrc7zfk+41btw44uPj9Y+IiIhnfEVFj42NDSdPnuTkyZPY2NiYOhwhihSZ+EuIp3E3BPZP1213mg6OnkYv0tXVVb+OxyOJiYn5mnyqbNmyREZG6u8XHR2d53tZW1tnS3hKGnNzcxo3bmzqMIQokqSGQ4j80mQ8bEpJhxqdoN6rBVJs48aNOXbsmP55WFgYarUaV1fXXK9p3rx5lpqIY8eO4eXlleP9AgMDKV++vBEiF0IISTiEyL8jc+HOObBxhm5zC2yCr9atW5OQkMCvv/4KwLRp02jfvj3m5uY8ePAAjUaT7Zo6derw/vvvc+LECZYtW8a3337LkCFDAOjTpw+rVq0iKCiIpKQk5s2bR8eOHQvktRRV6enpzJo1i1mzZpGenm7qcIQoUmRqcyHyIyoYFgaANgNeXAR+fQu0+E2bNtG/f39sbW0xMzNj//79+Pj4oFKpCAwMpF69elnOf/DgAYMGDWLnzp2ULVuWMWPG6BMOgM8++4xvvvkGGxsbqlevzqFDh/K87LpMbS5TmwuRH5JwCJFXmgxY1BaigqBWN3jlN5NMXx4VFcWZM2do1qwZpUuXfub7hYSEEBkZSZs2bfLVH0QSDkk4hMgPSTiEyKv9M3QdRW1dYOgJKOVu6ohMShIOSTiEyA/pwyFEXty5AAdn6ba7fFPikw0hhMgvSTiEeJLMdN2oFG0m1O4BdfuYOiIhhChyJOEQ4kkOzoK7wWBXGrrOlmXnhRDiKUjCIcTj3A6EQ9/qtrt+Cw5upo1HCCGKKJlpVIjcZKph/RBQNFCnt+4hSjQbGxv27dun3xZC5J0kHELkZv8MiL4E9m7Q5VtTRyMKAXNzcwICAkwdhhBFkjSpCJGTW2d0M4oCdJsD9s8+34UQQpRkUsMhxH9lpOlGpSha8H0Zanc3dUSikMjIyGDhwoUAvPfee1haWpo4IiGKDpn4S4j/2jURjnwHDu4w9DjY5b44WkkmE3/JxF9C5Ic0qQjxbxEn4eh83Xa3uZJsCCGEgUjCIcQjGan/NKX49YNaXUwdkRBCFBuScAjxyN4pcP8aOHhA5xmmjkYIIYoVSTiEALh5HI4t0G33mKdboE0IIYTBSMIhRHqKrikFBeq9BjU6mjoiIYQodiThEGLvVxD7NziWh45TTR2NEEIUSzIPhyjZbhyF4z/qtnvMA1tnk4YjCjdra2u2bNmi3xZC5J0kHKLkSk/+pyml/utQrb2pIxKFnIWFBV27djV1GEIUSdKkIkqu3ZMhLhwcK0DHaaaORgghijWp4RAlU9ghOKmbopqe34NNyZgpUzybjIwMVqxYAcCAAQNkanMh8kGmNhcljzoJfmwOD25Cw0HQfa6pIyqSZGpzmdpciPyQJhVR8uyaqEs2nCpBh69MHY0QQpQIknCIkuX6Pji9RLfd83uwLmXaeIQQooSQhEOUHGkJsOlD3Xbjd6BKG9PGI4QQJYgkHKLk2DUB4iPA2Qvaf2HqaIQQokSRhEOUDNf2wJmluu2eC8DawaThCCFESSMJhyj+0uL/aUppOhi8W5k2HiGEKIFkHg5R/O0cDwmR4OINz080dTSiCLO2tmbNmjX6bSFE3knCIYq3K39B4G+ACnr9AFYyb4J4ehYWFrz88sumDkOIIkmaVETxlRoHm4frtpsNBa8Wpo1HCCFKMKnhEMXXjvGQeAdKV4N2n5s6GlEMZGZmsn79egB69+6NhYV8hAqRV/LXIoqny9vh/O+gMoNeP4KVnakjEsWAWq2mb9++gG5qc0k4hMg7aVIRxU9KLGweodtuPgwqNjFtPEIIISThEMXQ9jGQdBfK1IC2n5k6GiGEEEjCIYqbS1sgaM0/TSmWtqaOSAghBJJwiOIk+T5sGanbfm4EVGhk0nCMITg4mMaNG+Pi4sLo0aNRFOWJ13zxxRe4urpibW1N7969SUxM1B/z8/NDpVLpH++8844xwxdClGCScIjiY/toSI4Gt9oQMM7U0RicWq2me/fuNGzYkNOnTxMSEsLSpUsfe82KFStYsWIFO3bs4OLFi1y6dIkZM2YAkJKSwvXr17l37x5xcXHExcUxf/78AnglQoiSSBIOUTyEbITgdaAy103wZVH8ZoHcvn078fHxzJ49m6pVqzJt2jSWLFny2GsiIiJYtmwZTZo0oVq1arzyyisEBgYCEBgYiJ+fH25ubjg7O+Ps7IytrTRBCSGMQ8Z0iaIvOQa2fKTbbjkKyjcwbTxGcv78eZo1a4adnW6Ir5+fHyEhIY+9ZuzYsVmeX758merVqwNw8uRJbt26hZubGxkZGfTv35+5c+fmOmW3Wq1GrVbrnyckJDzLyymSrKys+PXXX/XbQoi8kxoOUfRt/RhSYqBsHWjzqamjMZqEhAS8vb31z1UqFebm5sTFxeXp+itXrrB+/Xree+89QJd8tGzZksOHD7Nz50527drFnDlzcr1++vTpODk56R8VK1Z8thdUBFlaWjJw4EAGDhyIpaWlqcMRokhRKXnpdSZEYRX8J6wdBGYW8M4e8Kxn6oiMZsyYMWRkZDB79mz9vooVK3L8+HHKly//2Gu1Wi2tW7fG39+fBQsW5HjO//73P+bNm8fp06dzPJ5TDUfFihWJj4/H0dHxKV6REKIkkSYVUXQl3dPVbgC0+qRYJxsArq6uBAcHZ9mXmJiYp6r9r776itjYWGbNmpXrOWXLliUyMjLX49bW1iV+hdTMzEx27twJQMeOHWWmUSHyQZpURNGkKLBlFKTGgrsvtPrY1BEZXePGjTl27Jj+eVhYGGq1GldX18det3nzZmbPns26dev0/T8AmjdvTkREhP75sWPH8PLyMnzgxYharaZbt25069YtS22PEOLJJOEQRVPwOgjdomtK6f0jWBT/DnytW7cmISFB32lx2rRptG/fHnNzcx48eIBGo8l2zaVLl+jfvz/z58+nYsWKJCUlkZKSAkCdOnV4//33OXHiBMuWLePbb79lyJAhBfqahBAlh/ThEEVPYhQsaAppD3RTlxfjjqL/tWnTJvr374+trS1mZmbs378fHx8fVCoVgYGB1KtXL8v5o0aNYu7cuVn2eXl5ER4ezoMHDxg0aBA7d+6kbNmyjBkzJl8JR0JCAk5OTiWqD0dycjIODg6AbvE2e3t7E0ckRNEhCYcoWhQFVr0Kl7dBOX9dR1HzkjVaICoqijNnztCsWTNKly5tsjgk4ZCEQ4j8kB5Pomi5sEaXbJhZ6tZKKWHJBoCHhwddu3Y1dRhCCJEv0odDFB0Jd3TTlwMEjAX3OqaNRwghRJ5JwiGKBkWBzSMgLR4868NzI00dkRBCiHyQJhVRNJz7Ha7uBHOrh00p8l9XFDwrKyu+//57/bYQIu+k06go/OIj4YdmoE6A9pN166UIkyuJnUaFEE9PmlRE4aYosHm4Ltko3wiaf2jqiIQQQjwFqZcWhVvgcri2G8ytpSlFmJxGo+HQoUMAtGrVCnNzcxNHJETRIZ/eovB6EAE7xuu2n58AbjVMG48o8dLS0mjbti0g83AIkV/SpCIKJ0WBTR9CeiJUbArNhpo6IiGEEM9AEg5ROJ35Ff7eBxY20PMHMJOqayGEKMok4RCFT9wN+GuCbvv5SVCmmmnjEUII8cwk4RCFi1YLmz6A9CSo1AKaDjZ1REIIIQxAEg5RuJxeAmEHwdIOen4PZvJfVAghigP5NBeFR2wY7Jqk224/GUpXNWk4QgghDEeGxYrCQauFjR9ARjJ4tYTG75o6IiGysbS0ZObMmfptIUTeydTmonA48TNs/xQs7WHIEXD1NnVE4glkanMhRH5Ik4owvfvXYfdk3XaHLyXZEEKIYkiaVIRpabWwcRhkpIB3a2j4lqkjEiJXGo2Gs2fPAtCgQQOZ2lyIfJCEQ5jWiZ/g5jGwcoCeC2RUiijU0tLSaNKkCSBTmwuRX/LpLkwn5hrs+UK33WEKOFcybTxCCCGMRhIOYRpaDWwYAplpUKUtNBxo6oiEEEIYkSQcwjSO/wC3ToJVKegxH1QqU0ckhBDCiCThEAUv+grs+Uq33WkaOFc0bTxCCCGMThIOUbA0mbqmFI0aqrWH+q+bOiIhhBAFQBIOUbCOzYfI02DtCN3nSVOKEEKUEDIsVhSce5dg3zTddqcZ4FTetPEIkU+WlpZMmjRJvy2EyDuZ2lwUDE0mLGkPtwOhekd4dbXUbhRxMrW5ECI/pElFFIwjc3XJho0TdP9Okg0hhChhpElFGN/di7B/hm678yxwLGfaeIR4SlqtlkuXLgFQu3ZtzGRmXCHyTBIOYVyaDFg/GLQZULMr+PU1dURCPLXU1FTq1q0LyNTmQuSXpOfCuA7NhqgLYOsC3eZIU4oQQpRQknAI47lzAQ7O1G13+QZKuZs2HiGEECYjCYcwjsx02DAUtJlQqxvU7WPqiIQQQpiQJBzCOA59A3eDwK40dJsrTSlCCFHCScIhDO/2OTj4jW67yzfg4GbScIQQQjyZWq3GmFNzScIhDCtTrVsrRdGATy+o+6KpIxJCCPEEEREReHl50bRpU3bu3GmUxEMSDmFYB2bCvRCwKwNdvzV1NMVOcHAwjRs3xsXFhdGjR+fpQ2Ht2rV4eXnh6enJypUrsxxbsGAB7u7uVKlShb179xor7GLD0tKSTz75hE8++USmNhfFSnR0NHfv3uXMmTN06tTJOImHIoSh3DqtKJNdFGWSo6Jc3GDqaIqdtLQ0pXLlysr777+vXLt2TenSpYvyyy+/PPaaoKAgxcrKSlm0aJFy4cIFpVq1akpoaKiiKIqyY8cOxcbGRtmwYYNy5MgRxdvbW4mJiclzPPHx8QqgxMfHP9PrEkKY3pkzZxRA/zA3N1cApXHjxsqOHTsUrVb7zGUYdS0VRVFITEw01u1FYZKRBr92gftXoHYP6PWDqSMqdrZs2cKwYcO4dOkSdnZ2BAUF8fHHH/PXX3/les2YMWO4evUqf/75JwA//vgjMTExTJgwgf79++Pu7s7cuXMBGDt2LLVr1+bNN9/M8V5qtRq1Wq1/npiYiI+PDxEREbKWihBF3Llz52jTpk22/WZmZmi1Who3bsy0adNo3779U5dh1IQjOjqasmXLGuv2QgghhCggtWvXJiQk5KmvN+rU5lZWVgAl7hdQQkICFStWlNddQhTU6x4/fjxqtZpvv/2nb4y3tzdnz57FxcUlx2tat27NqFGj6N27NwCXLl3i7bff5ujRo1SuXJl169bRsGFDAHbu3Mmvv/7KqlWrcrzXf2s4EhISqFOnDjdv3sTJyclQL7PQk//n8rqLo7zWcDwLoyYcqodzLzg6Ohbrf6jcyOsuWYz9uu3t7bGysspShp2dHRYWFrmWa21tjYuLi/54mTJlUKvVODo6YmlpSenSpfXHXF1dycjIyPNrSEhIAMDp/+3dW0iTbxwH8K+puTnx7yHdIkEMhNpFSnawo5TQCiSkAyVBF2VREHWbCZl00UWWKWlJRF7WRXiIoBC0UNAMUbODRjAhDdNi5Smcye9/EXvRLd17nD3z94FdvJuP/X58fd730d7t+e8/znsJ4b6DU1RU1Jzj0NBQzMzMIC0tDdeuXcOePXuka7pa/C4VxgQRFxeHkZGROc+NjY1Jf0mUM2b21y/0GmNsafLsgLxu3ToAQFNTExwOh+bFBsALDsaEsXHjRrS2tkrHTqcTU1NTiIuLkz2ms7MTq1at8vsaY2xpSUxMhM1mQ0ZGBp49e4ampiYA0GWh4WHogiMiIgJFRUWIiIgw8p/553Df3LcRdu7cidHRUTx48AAApDvGQ0ND8ePHD8zMzPiMOXjwIB4+fIienh6Mj4+jvLwcDocDAHDo0CFUVlZicHAQX79+xf3796XX5OC8ue+lYKn0nZSUhP7+frx69QoOhwMmk0n3vg19lwpjTF/19fXIy8uD2WzGsmXL8OLFC9jtdoSEhKCzsxPp6ek+YwoLC1FSUgKTyYTU1FQ0NzfDbDaDiHD8+HE8fvwYAJCdnY36+npdf6NhjDEPXnAwJpihoSF0dHQgMzMT8fHxssa8f/8eg4ODyMrK8rlP4/Xr15iYmEBWVhYvNhhjhuEFB2OMMcYMxzeNMsYYY8xwvOBgjDHGmOF0WXDU1dVh9erVCAsLQ3p6Oj58+CBr3MuXL7F27VqsWLECN2/e1KOUgPv27RtSUlLQ398ve8z+/fsREhIiPbR8Nv1iUdO36Hmr2akV+PN+9tl55+fnG1ypPvTemVYUavoWNWNvSue16HPaQ2nfwXAOV3Pd1py31t3fPn36RLGxsfTo0SMaGhqiw4cP09atW/2OGx4epujoaCouLqaPHz/S+vXrqbGxUWs5ATUyMkKbN28mAOR0OmWPW7lyJfX09JDL5SKXy0Xj4+PGFWkANX2LnreanVqJiCYmJigyMpKGh4elvCcnJwNQsTZ670wrCjV9i5qxN6XzWvQ57aHmfCb6OVzNdVuPvDUvOJ48eUJVVVXScWNjI5nNZr/jSktLac2aNdKWt7W1tXTs2DGt5QRUdnY2lZWVKfpBHRgYIJvNZmxhBlPTt+h519TUUGxsLE1MTBARUVdXF23bts3vuJaWFsrMzDS6PN2p6ffChQvkcDik41u3blFhYaGhdepNTd+iZuxN6bwWfU57KO07GM7haq7beuSt+b9UcnJycPr0aem4r68Pqampfsd1d3dj165d0tvwNm3ahI6ODq3lBNS9e/dw/vx5RWPa29sxMzODpKQkWCwWHD16FC6Xy6AKjaGmb9Hz7u7uRmZmJiIjIwH8+RO6nF0T29vbMTAwgISEBMTExODs2bNzNkD7V6npt7u7G7t375aORcsYUNe3qBl7UzqvRZ/THkr7DoZzuJrrth55y15w5ObmIiYmxudx+/Zt6Wvcbjdu3LiBM2fO+P1+o6OjSElJkY6jo6Px5csXRcUHwkJ9z65frt7eXqSlpeHp06doa2uD0+lEQUGBAZVro3ffouddXl4+p/6QkBCEhob6PdH09fVh+/btaGlpwfPnz9HQ0IDS0lKj29DMOy85/YqS8ULU9C1qxt6UzutgyBtQ3rco53C55F639chb9m6xVVVV+PXrl8/zs/dxKCoqgsVikXXDVFhY2JyPTDWZTJicnJRbTsDI6VuJgoKCOT+c169fx4EDB3D37l3VNRpB775Fz7usrMznQ7E8Pcy3NTwAn1wvX76M8vJyXLx4UZ+CDeKdF+C/X1EyXoiavkXNWKtgyFsNUc7hcsm9buuRt+wFh9VqXfD1xsZGVFRUoK2tDeHh4X6/nyg7VfrrW6vExER8//4dU1NT/9Rn9evdt+h522w2vH37ds5zanpITEzE4OCg6voCJS4uTnG/omS8EDV9exMlY62CIW89/KvncDmUXLf1yFuXt8U6nU7k5eWhoqICdrtd1pilulPlkSNH0NLSIh23trbCarUK94OqlOh5q9mpFQC2bNmCz58/S8etra1ITk42rE696L0zrSjU9C1qxloFQ95qBMs5XOl1W5e8ld/fOtfk5CTZ7XY6deoUjY2NSQ/Pnaw/f/4kt9vtM25kZIRMJhM1NDSQ2+2mvXv30rlz57SWsyjwl7ub5+v76tWrtGHDBmpubqaamhqyWq105cqVAFWqLyV9i5739PQ0JSQkSG+RzM/Pp5ycHOl1l8tFv3//9hl38uRJ2rdvH7W1tVF1dTVZLBaqrq4OWN1qLdTvfL12dXWRxWKhN2/e0NjYGKWnp1NJSUlA69ZKTd+iZjwf73kdrHPam9y+g+EcvtB128i8NS84amtrCYDPwxNccnIy1dTU/HXsnTt3KDw8nGJjYyklJYWGhoa0lrMo/nbhna9vt9tNJ06cIIvFQjabjYqLi2l6ejowhepMSd9E4uddV1dHkZGRFB8fTwkJCfTu3TvpNQDU2dnpM8blclFubi6ZzWZKTk6mysrKAFaszXz9ztcrEdGlS5do+fLlFB0dTRkZGUJ+HoXSvkXO+G+853Uwz+nZ5PYdDOfwha7bRua96Ju3OZ1O9Pb2YseOHYiKilrMUlgAiJ63mp1aRab3zrSiWGo5ayH6nGbKaMl70RccjDHGGAt+vHkbY4wxxgzHCw7GGGOMGY4XHIwxxhgzHC84GGOMMWY4XnAwxhhjzHC84GCMMcaY4XjBwRhjjDHD8YKDMcYYY4bjBQdjjDHGDPc/0k2JhB/K7kUAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(-1, 1., 50)\n",
    "y = x ** 2 + 1\n",
    "y1 = x + 1\n",
    "plt.xlim(-2, 2)\n",
    "plt.ylim(0, 2)\n",
    "plt.plot(x, y, label='$y = x^2 + 1$')\n",
    "plt.plot(x, y1, label='$y = x + 1$')\n",
    "ax = plt.gca()\n",
    "ax.spines['right'].set_color('none')\n",
    "ax.spines['top'].set_color('none')\n",
    "ax.xaxis.set_ticks_position('bottom')\n",
    "ax.yaxis.set_ticks_position('left')\n",
    "ax.spines['bottom'].set_position(('data', 0))\n",
    "ax.spines['left'].set_position(('data', 0))\n",
    "ax.plot(1, 0, \">k\", transform=ax.get_yaxis_transform(), clip_on=False)\n",
    "ax.plot(0, 1, \"^k\", transform=ax.get_xaxis_transform(), clip_on=False)\n",
    "plt.legend(loc='best')\n",
    "x0 = 0.5\n",
    "y0 = x0 **2 + 1\n",
    "plt.scatter(x0, y0)\n",
    "plt.plot([x0, x0], [y0, 0], linestyle='--', color='k')\n",
    "plt.annotate(\"$x0^2 + 1 = y0$\", [x0, y0],xytext=[+30, -30], textcoords='offset points',\n",
    "             arrowprops=dict(arrowstyle='->', connectionstyle='arc3, rad=.2'))\n",
    "plt.text(-2, 1, '$x_i + y^i + \\sigma + \\\\theta + \\sum_{i=1}^n a_i^2 + b_i^2$')\n",
    "# for label in ax.get_xticklabels() + ax.get_yticklabels():\n",
    "#     label.set_fontsize(12)\n",
    "#     label.set_bbox(dict(facecolor='white',edgecolor='None', alpha=0.7))\n",
    "plt.title(\"调整坐标轴位置、坐标轴加箭头、标注（支持latex）\",fontsize=10)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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693//dxUUFGju3Lk+V35yc3M1fvx47d69Wx999JHPk2JDQ0P1ySefaNeuXWrVqpW2b9+ukpISn68AX6yyslJ/+9vftHbtWi1btkwJCQn6wx/+oF/84he1riBVVFToscce07Zt23T48GGdOnVK48aN06RJk9S/f3/16tVL7du3V9u2bRUeHq4jR47o8OHDqqioUGlpqTIzMxUREaFnn31W0dHRuvfee73brqmp8T6CPzc3V0888YTy8vK0cuVKn34AGhDgkASgmf785z+bDz74oNYVj/T0dNOmTRvTr18/8+CDD5rJkyebF154wdxxxx3m1ltvNcYYU1NTY1wul/eqwODBg82wYcO8r33XkSNHTGRkpLn11lvNO++8U289s2bNMq1atTIPP/yw9+vR35WdnW3i4uLMuHHjvOsee+wx43A4TI8ePcz27dtrjXnzzTdN27ZtvV/lDQkJMWlpaT5fr16xYoV5/PHHzX333WduvfVW07p1axMaGmoGDx5s/vznP9ean+8qLy83o0ePNqtWrfKuq6mpMevXrzdPPPGEuf32201SUpJp06ZNra8VjxkzxhhjzJ49e4zT6TTz5s3z2XZaWpr505/+ZA4ePGiioqLMLbfcYnbv3l1vLQBqcxhz0a9tAQhqJ06cUEJCgvfm2Atyc3N16tQppaenN3mbNTU1Plc46lJQUKC///3v3vte6vLZZ58pPj5e119/vSTp8OHD2rFjh+655x7vjxQ2VW5urn75y18qOTlZN9xwg/r06aO0tDTFxcU1a3v1qa6u1rlz51RVVaXq6mo5nU61bt1akrR//34lJyfX+bC6CzX+4Ac/aPZ7BK5VhBQAAGAlvoIMAACsREgBAABWIqQAAAArEVIAAICVgvY5KTU1NTp+/Ljatm3b4NMzAQCAPYwxKi0tVadOnS75rcGgDSnHjx/3+SVSAAAQPAoLC9WlS5cG+wRtSGnbtq0kqVBSdGBLAQAAjeSW1FXf/h1vSNCGlAsf8USLkAIAQLBpzK0a3DgLAACsREgBAABWIqQAAAArEVIAAICVCCkAAMBKhBQAAGAlQgoAALASIQUAAFiJkAIAAKxESAEAAFYipAAAACsRUgAAgJWC9gcGr7QjkooCXUSQaCepW6CLwGXheAdQl0Cf3wkpdTgiqYeks4EuJEhESNongkqw4ngHUJ9An9/5uKcOReKE3RRnxb/CgxnHO4D6BPr8TkgBAABWIqQAAAArEVIAAICVCCkAAMBKhBQAAGAlQgoAALASIQUAAFiJkAIAAKxESAEAAFYipAAAACsRUgAAgJUIKQAAwEqEFAAAYCVCCgAAsBIhBQAAWImQAgAArERIAQAAViKkAAAAKxFSAACAlQgpAADASoQUAABgJUIKAACwkl9DSlFRkZKTk3X48OFG9d+yZYt69uypdu3aac6cOf4sBQAABDm/hZSioiLdfffdjQ4op0+fVkZGhsaMGaPs7GytWLFCmzdv9lc5AAAgyPktpIwePVo//elPG91/xYoV6tSpk2bMmKHu3btr5syZWrJkib/KAQAAQc5vIWXx4sWaOHFio/vn5eVp8ODBcjgckqQ+ffooJyen3v4ej0dut9unAQCAlstvISU5OblJ/d1ut8+Y6OhoHT9+vN7+s2fPVkxMjLd17dq12bUCAAD7BezbPWFhYXI6nd7liIgIlZeX19t/2rRpKikp8bbCwsKrUSYAAAiQsEDtOD4+XqdPn/Yul5aWKjw8vN7+TqfTJ9QAAICWLWBXUlJTU5Wdne1dzs3NVefOnQNVDgAAsMwVDylut1uVlZW11mdkZGjbtm3atGmTKisr9fzzzys9Pf1KlwMAAILEFQ8pKSkpev/992utb9eunbKysjR06FB16NBB+/bt029+85srXQ4AAAgSfr8nxRjjs9zQw90mTJig9PR07d27VwMGDFBUVJS/ywEAAEEqYDfOXpCcnNzkry8DAICWjx8YBAAAViKkAAAAKxFSAACAlQgpAADASoQUAABgJUIKAACwEiEFAABYiZACAACsREgBAABWIqQAAAArEVIAAICVCCkAAMBKhBQAAGAlQgoAALASIQUAAFiJkAIAAKxESAEAAFYipAAAACsRUgAAgJUIKQAAwEqEFABoAk6auJZESGoXwP2HBXDfABB0aiT9RVLPQBcCXAXtJHUL4P4JKQDQRD0l3RroIoBrAFcuAQCAlQgpAADASoQUAABgJUIKAACwEiEFAABYiZACAACsREgBAABWIqQAAAArEVIAAICVCCkAAMBKhBQAAGAlQgoAALASIQUAAFiJkAIAAKxESAEAAFYipAAAACsRUgAAgJUIKQAAwEqEFAAAYCVCCgAAsBIhBQAAWImQAgAArERIAQAAViKkAAAAKxFSAACAlQgpAADASoQUAABgJUIKAACwEiEFAABYiZACAACsREgBAABWIqQAAAArEVIAAICVCCkAAMBKhBQAAGAlv4WU/Px8paamKi4uTpMnT5Yx5pJjUlJS5HA4vG3cuHH+KgcAAAQ5v4QUj8ej4cOHq3fv3tqxY4cKCgq0bNmyBseUl5frwIEDOnXqlFwul1wulxYsWOCPcgAAQAvgl5Cybt06lZSUaM6cOfre976nWbNmacmSJQ2Oyc3NVUpKihITExUbG6vY2Fi1bt3aH+UAAIAWwC8hJS8vT2lpaYqMjJR0/mOcgoKCBsds375dR48e9YaUzMxMeTyeevt7PB653W6fBgAAWi6/hBS3263k5GTvssPhUGhoqFwuV71j9u3bp/79+2vr1q3asGGDNm7cqKysrHr7z549WzExMd7WtWtXf5QOAAAs5ZeQEhYWJqfT6bMuIiJC5eXl9Y55+eWX9dprr6lHjx7653/+Z82cOVNvvfVWvf2nTZumkpISbyssLPRH6QAAwFJh/thIfHy88vPzfdaVlpYqPDy80dto3769jh07Vu/rTqezVhACAAAtl1+upKSmpio7O9u7fOjQIXk8HsXHx9c7pm/fvj5XQ7Kzs5WUlOSPcgAAQAvgl5AycOBAud1uLV26VJI0a9YsDRkyRKGhoSouLlZ1dXWtMb169dL48eP16aefavny5XrxxReVmZnpj3IAAEBLYPxkzZo1JjIy0iQkJJjExESze/duY84/0c3k5ubW6u9yucyIESNM69atTVJSklm4cGGT9ldSUmIkmRLJGD+3HMmI1qSWcwX+O9CuTuN453in0a5mK9H5/x+VlJRc8m+9X+5JkaSMjAwdOHBAOTk5SktLU0JCgiTpfE6pLTY2VqtXr/bX7gEAQAvjt5AiSdddd52GDRvmz00CAIBrFD8wCAAArERIAQAAViKkAAAAKxFSAACAlQgpAADASoQUAABgJUIKAACwEiEFAABYiZACAACsREgBAABWIqQAAAArEVIAAICVCCkAAMBKhBQAAGAlQgoAALASIQUAAFiJkAIAAKxESAEAAFYipAAAACsRUgAAgJUIKQAAwEqEFAAAYCVCCgAAsBIhBQAAWImQAgAArERIAQAAViKkAAAAKxFSAACAlQgpAADASoQUAABgJUIKAACwEiEFAABYiZACAACsFBboAtAy7Al0AWg2/ts1HXOGa0U7Sd0CuH9CCi5biKQHA10EcBVxvONaESFpnwIXVPi4B5etJtAFAACuiLOSigK4f0IKAACwEiEFAABYiZACAACsREgBAABWIqQAAAArEVIAAICVCCkAAMBKhBQAAGAlQgoAALASIQUAAFiJkAIAAKxESAEAAFYipAAAACsRUgAAgJUIKQAAwEqEFAAAYCVCCgAAsBIhBQAAWImQAgAArERIAQAAViKkAAAAKxFSAACAlfwaUvLz85Wamqq4uDhNnjxZxphLjnnrrbeUlJSkTp066bXXXvNnOQAAIIj5LaR4PB4NHz5cvXv31o4dO1RQUKBly5Y1OCY/P19jx47VjBkztGHDBs2cOVP79u3zV0kAACCYGT9ZvXq1iYuLM2VlZcYYY3bu3Gn69evX4JhJkyaZ9PR07/LcuXPN9OnTG7W/kpISI8mUSMb4ueVIRjQajUaj0UyO/Ps3tuQf2y0pKbnk33q/XUnJy8tTWlqaIiMjJUkpKSkqKCi45Jg77rjDu9ynTx/l5OTU2dfj8cjtdvs0AADQcvktpLjdbiUnJ3uXHQ6HQkND5XK5Gj0mOjpax48fr7Pv7NmzFRMT421du3b1V+kAAMBCfgspYWFhcjqdPusiIiJUXl7e6DEN9Z82bZpKSkq8rbCw0D+FAwAAK4X5a0Px8fHKz8/3WVdaWqrw8PAGx5w+fbpR/Z1OZ60QBAAAWi6/XUlJTU1Vdna2d/nQoUPyeDyKj49v9Jjc3Fx17tzZXyUBAIAg5reQMnDgQLndbi1dulSSNGvWLA0ZMkShoaEqLi5WdXV1rTEjR47U66+/rl27dunMmTOaP3++0tPT/VUSAAAIZo36vm8jrVmzxkRGRpqEhASTmJhodu/ebYwxRpLJzc2tc8yvf/1rEx4ebqKjo03v3r1NeXl5o/bFV5BpNBqNRrvyLZBfQXb8I0T4zcmTJ5WTk6O0tDQlJCQ0akxBQYGOHTumQYMGNXgPy3e53W7FxMSoRFL0ZdRbl88k9fbzNgEACEY5km714/bckmIklZSUKDq64b/gfg8pVwshBQCAKy+QIYUfGAQAAFYipAAAACsRUgAAgJUIKQAAwEqEFAAAYCVCCgAAsBIhBQAAWImQAgAArERIAQAAViKkAAAAKxFSAACAlQgpAADASoQUAABgJUIKAACwEiEFAABYiZACAACsREgBAABWIqQAAAArEVIAAICVCCkAAMBKhJQ6tJMUEegiAABXBH/4gkdYoAuwUTdJ+yQVBboQ4CrYI+nBQBcRZP4iqWegi0CzcLwHF0JKPbr9owHAxXpKujXQRQDXAK56AQAAKxFSAACAlQgpAADASoQUAABgJUIKAACwEiEFAABYiZACAACsREgBAABWIqQAAAArEVIAAICVCCkAAMBKhBQAAGAlQgoAALASIQUAAFiJkAIAAKxESAEAAFYipAAAACsRUgAAgJUIKQAAwEqEFAAAYCVCCgAAsBIhBQAAWImQAgAArERIAQAAViKkAAAAKxFSAACAlQgpAADASoQUAABgJUIKAACwEiEFAABYiZACAACsREgBAABWIqQAAAArEVIAAICVCCkAAMBKfgkp+fn5Sk1NVVxcnCZPnixjTKPGpaSkyOFweNu4ceP8UQ4AAGgBLjukeDweDR8+XL1799aOHTtUUFCgZcuWXXJceXm5Dhw4oFOnTsnlcsnlcmnBggWXWw4AAGghLjukrFu3TiUlJZozZ46+973vadasWVqyZMklx+Xm5iolJUWJiYmKjY1VbGysWrdufbnlAACAFuKyQ0peXp7S0tIUGRkp6fxHOAUFBZcct337dh09etQbUjIzM+XxeOrt7/F45Ha7fRoAAGi5Gh1SRowY4b3i8d02f/58JScne/s5HA6FhobK5XI1uL19+/apf//+2rp1qzZs2KCNGzcqKyur3v6zZ89WTEyMt3Xt2rWxpQMAgCDkMI28y/Wrr75SRUVFrfXz5s2Tw+HQnDlzvOu6du2qTz75RJ07d250If/93/+t+fPna8eOHXW+7vF4fK60uN1ude3aVSWSohu9FwAX+0xS70AXEWRyJN0a6CLQLBzvTefv490tKUZSSUmJoqMb/gse1tiNdujQoc711113nfLz833WlZaWKjw8vLGbliS1b99ex44dq/d1p9Mpp9PZpG0CAIDgddn3pKSmpio7O9u7fOjQIXk8HsXHxzc4rm/fviosLPQuZ2dnKykp6XLLAQAALcRlh5SBAwfK7XZr6dKlkqRZs2ZpyJAhCg0NlSQVFxerurq61rhevXpp/Pjx+vTTT7V8+XK9+OKLyszMvNxyAABAS2H8YM2aNSYyMtIkJCSYxMREs3v3bu9rkkxubm6tMS6Xy4wYMcK0bt3aJCUlmYULFzZpnyUlJUaSKZGModFozW45khGtSS3Hgv9uNI73YD3eS/6x3ZKSkkv+rW/0PSkNycjI0IEDB5STk6O0tDQlJCR4XzufU2qLjY3V6tWr/bF7AADQAvklpEjnb6AdNmyYvzYHAACucfzAIAAAsBIhBQAAWImQAgAArERIAQAAViKkAAAAKxFSAACAlQgpAADASoQUAABgJUIKAACwEiEFAABYiZACAACsREgBAABWIqQAAAArEVIAAICVCCkAAMBKhBQAAGAlQgoAALASIQUAAFiJkAIAAKxESAEAAFYipAAAACsRUgAAgJUIKQAAwEqEFAAAYCVCCgAAsBIhBQAAWImQAgAArERIAQAAViKkAAAAKxFSAACAlQgpAADASoQUAABgJUIKAACwUligC7DVEUlFgS4CuAr2BLoAAKgHIaUORyT1kHQ20IUAV0mIpJpAFwEAF+HjnjoUiYCCawsBBYCNCCkAAMBKhBQAAGAlQgoAALASIQUAAFiJkAIAAKxESAEAAFYipAAAACsRUgAAgJUIKQAAwEqEFAAAYCVCCgAAsBIhBQAAWImQAgAArERIAQAAViKkAAAAKxFSAACAlQgpAADASoQUAABgJUIKAACwEiEFAABYiZACAACsREgBAABW8ltIKSoqUnJysg4fPtzoMVu2bFHPnj3Vrl07zZkzx1+lAACAFsAvIaWoqEh33313kwLK6dOnlZGRoTFjxig7O1srVqzQ5s2b/VEOAABoAfwSUkaPHq2f/vSnTRqzYsUKderUSTNmzFD37t01c+ZMLVmyxB/lAACAFsAvIWXx4sWaOHFik8bk5eVp8ODBcjgckqQ+ffooJyen3v4ej0dut9unAQCAlqvRIWXEiBGKjY2t1V566SUlJyc3ecdut9tnXHR0tI4fP15v/9mzZysmJsbbunbt2uR9AgCA4BHW2I6LFi1SRUVFrfXx8fHN23FYmJxOp3c5IiJC5eXl9fafNm2afvWrX3mX3W43QQUAgBas0SGlQ4cOft1xfHy8Tp8+7V0uLS1VeHh4vf2dTqdPqAEAAC1bwJ6TkpqaquzsbO9ybm6uOnfuHKhyAACAZa54SHG73aqsrKy1PiMjQ9u2bdOmTZtUWVmp559/Xunp6Ve6HAAAECSueEhJSUnR+++/X2t9u3btlJWVpaFDh6pDhw7at2+ffvOb31zpcgAAQJBo9D0pjWGMqbWuoQe8TZgwQenp6dq7d68GDBigqKgof5YDAACCmF9DSnMkJyc36yvMAACgZeMHBgEAgJUIKQAAwEqEFAAAYCVCCgAAsBIhBQAAWImQAgAArERIAQAAViKkAAAAKxFSAACAlQgpAADASoQUAABgJUIKAACwEiEFAABYiZACAACsREgBAABWIqQAAAArEVIAAICVCCkAAMBKhBQAAGAlQgoAALASIaUO7SRFBLoIAFaK0PlzBIIT5/emCfTxHhbAfVurm6R9kooCXQgA67TT+XMEghPn96YJ9PFOSKlHN3EiAoCWiPN78ODjHgAAYCVCCgAAsBIhBQAAWImQAgAArERIAQAAViKkAAAAKxFSAACAlQgpAADASoQUAABgJUIKAACwEiEFAABYiZACAACsREgBAABWCtpfQTbGSJLcAa4DAAA03oW/2xf+jjckaENKaWmpJKlrgOsAAABNV1paqpiYmAb7OExjooyFampqdPz4cbVt21YOhyPQ5VwVbrdbXbt2VWFhoaKjowNdzjWDeb/6mPPAYN4D41qbd2OMSktL1alTJ4WENHzXSdBeSQkJCVGXLl0CXUZAREdHXxMHsm2Y96uPOQ8M5j0wrqV5v9QVlAu4cRYAAFiJkAIAAKxESAkiTqdTv/3tb+V0OgNdyjWFeb/6mPPAYN4Dg3mvX9DeOAsAAFo2rqQAAAArEVIAAICVCCkAAMBKhBQAAGAlQoqlioqKlJycrMOHDzd6zJYtW9SzZ0+1a9dOc+bMuXLFtVD5+flKTU1VXFycJk+e3KjflZCklJQUORwObxs3btwVrrRlaM58v/XWW0pKSlKnTp302muvXYUqW5bmzDnHt3809ZzO+fw8QoqFioqKdPfddzcpoJw+fVoZGRkaM2aMsrOztWLFCm3evPnKFdnCeDweDR8+XL1799aOHTtUUFCgZcuWXXJceXm5Dhw4oFOnTsnlcsnlcmnBggVXvuAg15z5zs/P19ixYzVjxgxt2LBBM2fO1L59+65OwS1Ac+ac49s/mnpO53z+HQbWufPOO828efOMJHPo0KFGjcnKyjI33nijqampMcYY884775ixY8dewSpbltWrV5u4uDhTVlZmjDFm586dpl+/fpcct3XrVpOWlnaly2txmjPfkyZNMunp6d7luXPnmunTp1/ROluS5sw5x7d/NPWczvn8W1xJsdDixYs1ceLEJo3Jy8vT4MGDvT+22KdPH+Xk5FyJ8lqkvLw8paWlKTIyUtL5S9wFBQWXHLd9+3YdPXpUiYmJio2NVWZmpjwez5UuN+g1Z77z8vJ0xx13eJc5xpumOXPO8e0fTT2ncz7/FiElQEaMGKHY2Nha7aWXXlJycnKTt+d2u33GRUdH6/jx4/4suUWob97nz5/vM38Oh0OhoaFyuVwNbm/fvn3q37+/tm7dqg0bNmjjxo3Kysq60m8j6F18vDZmvjnGL09z5pzj2z+aek7nWP9W0P4KcrBbtGiRKioqaq2Pj49v1vbCwsJ8HqkcERGh8vLyZtfXUtU37/PmzfP+q+WCC3MYFxdX7/Zefvlln+WZM2dq/vz5mjp1qn8KbqEuPl6lS883x/jlac6cc3wHBsf6twgpAdKhQwe/bi8+Pl6nT5/2LpeWlio8PNyv+2gJ6pv36667Tvn5+T7rmjOH7du317Fjx5pd37UiPj6+yfPNMX55mjPnF+P4vjo41r/Fxz0tRGpqqrKzs73Lubm56ty5cwArCi4Xz9+hQ4fk8XgueWWrb9++Kiws9C5nZ2crKSnpitXZUjRnvjnGL09z5pzjOzA41r9FSAkybrdblZWVtdZnZGRo27Zt2rRpkyorK/X8888rPT09ABUGp4EDB8rtdmvp0qWSpFmzZmnIkCEKDQ2VJBUXF6u6urrWuF69emn8+PH69NNPtXz5cr344ovKzMy8qrUHo4bmu765HjlypF5//XXt2rVLZ86c0fz58znGm6A5c87xfWVxPm+EQH+9CPVTHV9XS0pKMqtXr66z/3/+53+aVq1ambi4OJOcnGxOnjx55YtsQdasWWMiIyNNQkKCSUxMNLt37/a+Jsnk5ubWGuNyucyIESNM69atTVJSklm4cOFVrDi41Tff9c21Mcb8+te/NuHh4SY6Otr07t3blJeXX8WKg19T55zj278uPqdzPr80hzGNfKwmgsKhQ4e0d+9eDRgwQFFRUYEuJ+icPHlSOTk5SktLU0JCQqDLafGaM98FBQU6duyYBg0adM1+Tn85OMaDB+dziZACAACsxD0pAADASoQUAABgJUIKAACwEiEFAABYiZACAACsREgBAABWIqQAAAArEVIAAICVCCkAAMBK/w//LMTqeONnsgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x1 = [-0.8,-0.8,1.2,1.2,0.8,0.8,-1.2,-1.2]\n",
    "y1 = [1.2,0.2,0.2,-1.2,-1.2,-0.2,-0.2,1.2]\n",
    "x2 = [1.2,-0.2,-0.2,-1.2,-1.2,0.2,0.2,1.2]\n",
    "y2 = [1.2,1.2,-0.8,-0.8,-1.2,-1.2,0.8,0.8]\n",
    "plt.axes().set_facecolor('r')\n",
    "plt.fill(x1,y1,color='k')\n",
    "plt.fill(x2,y2,color='k')\n",
    "plt.title(\"绘制填充多边形\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0.98, '填充曲线下的面积')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.cbook as cbook\n",
    "\n",
    "x = np.linspace(0,5,50)\n",
    "y = x - np.random.random(50)\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, sharex=True, sharey=True)\n",
    "\n",
    "\n",
    "ax1.plot(x, y, lw=2)\n",
    "ax2.fill_between(x, min(y), y, alpha=0.7)\n",
    "\n",
    "for ax in ax1, ax2:\n",
    "    ax.grid(True)\n",
    "    ax.label_outer()\n",
    "\n",
    "\n",
    "fig.suptitle('填充曲线下的面积')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Fixing random state for reproducibility\n",
    "np.random.seed(1)\n",
    "\n",
    "Nsteps = 500\n",
    "t = np.arange(Nsteps)\n",
    "\n",
    "mu = 0.002\n",
    "sigma = 0.01\n",
    "\n",
    "# the steps and position\n",
    "S = mu + sigma*np.random.randn(Nsteps)\n",
    "X = S.cumsum()\n",
    "\n",
    "# the 1 sigma upper and lower analytic population bounds\n",
    "lower_bound = mu*t - sigma*np.sqrt(t)\n",
    "upper_bound = mu*t + sigma*np.sqrt(t)\n",
    "\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.plot(t, X, lw=2, label='walker position')\n",
    "ax.plot(t, mu*t, lw=1, label='population mean', color='C0', ls='--')\n",
    "ax.fill_between(t, lower_bound, upper_bound, facecolor='C0', alpha=0.4,\n",
    "                label='1 sigma range')\n",
    "ax.legend(loc='upper left')\n",
    "\n",
    "# here we use the where argument to only fill the region where the\n",
    "# walker is above the population 1 sigma boundary\n",
    "ax.fill_between(t, upper_bound, X, where=X > upper_bound, fc='red', alpha=0.4)\n",
    "ax.fill_between(t, lower_bound, X, where=X < lower_bound, fc='red', alpha=0.4)\n",
    "ax.set_xlabel('num steps')\n",
    "ax.set_ylabel('position')\n",
    "ax.set_title('填充均值加减标准差的区域，用where作为掩码选择性填充')\n",
    "ax.grid()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0.98, '在竖直方向进行填充')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y = np.arange(0.0, 2, 0.01)\n",
    "x1 = np.sin(2 * np.pi * y)\n",
    "x2 = 1.2 * np.sin(4 * np.pi * y)\n",
    "\n",
    "fig, [ax1, ax2, ax3] = plt.subplots(1, 3, sharey=True, figsize=(6, 6))\n",
    "\n",
    "ax1.fill_betweenx(y, 0, x1)\n",
    "ax1.set_title('between (x1, 0)')\n",
    "\n",
    "ax2.fill_betweenx(y, x1, 1)\n",
    "ax2.set_title('between (x1, 1)')\n",
    "ax2.set_xlabel('x')\n",
    "\n",
    "ax3.fill_betweenx(y, x1, x2)\n",
    "ax3.set_title('between (x1, x2)')\n",
    "\n",
    "fig.suptitle(\"在竖直方向进行填充\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import warnings\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "from matplotlib.collections import LineCollection\n",
    "\n",
    "\n",
    "def colored_line(x, y, c, ax, **lc_kwargs):\n",
    "    \"\"\"\n",
    "    Plot a line with a color specified along the line by a third value.\n",
    "\n",
    "    It does this by creating a collection of line segments. Each line segment is\n",
    "    made up of two straight lines each connecting the current (x, y) point to the\n",
    "    midpoints of the lines connecting the current point with its two neighbors.\n",
    "    This creates a smooth line with no gaps between the line segments.\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    x, y : array-like\n",
    "        The horizontal and vertical coordinates of the data points.\n",
    "    c : array-like\n",
    "        The color values, which should be the same size as x and y.\n",
    "    ax : Axes\n",
    "        Axis object on which to plot the colored line.\n",
    "    **lc_kwargs\n",
    "        Any additional arguments to pass to matplotlib.collections.LineCollection\n",
    "        constructor. This should not include the array keyword argument because\n",
    "        that is set to the color argument. If provided, it will be overridden.\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    matplotlib.collections.LineCollection\n",
    "        The generated line collection representing the colored line.\n",
    "    \"\"\"\n",
    "    if \"array\" in lc_kwargs:\n",
    "        warnings.warn('The provided \"array\" keyword argument will be overridden')\n",
    "\n",
    "    # Default the capstyle to butt so that the line segments smoothly line up\n",
    "    default_kwargs = {\"capstyle\": \"butt\"}\n",
    "    default_kwargs.update(lc_kwargs)\n",
    "\n",
    "    # Compute the midpoints of the line segments. Include the first and last points\n",
    "    # twice so we don't need any special syntax later to handle them.\n",
    "    x = np.asarray(x)\n",
    "    y = np.asarray(y)\n",
    "    x_midpts = np.hstack((x[0], 0.5 * (x[1:] + x[:-1]), x[-1]))\n",
    "    y_midpts = np.hstack((y[0], 0.5 * (y[1:] + y[:-1]), y[-1]))\n",
    "\n",
    "    # Determine the start, middle, and end coordinate pair of each line segment.\n",
    "    # Use the reshape to add an extra dimension so each pair of points is in its\n",
    "    # own list. Then concatenate them to create:\n",
    "    # [\n",
    "    #   [(x1_start, y1_start), (x1_mid, y1_mid), (x1_end, y1_end)],\n",
    "    #   [(x2_start, y2_start), (x2_mid, y2_mid), (x2_end, y2_end)],\n",
    "    #   ...\n",
    "    # ]\n",
    "    coord_start = np.column_stack((x_midpts[:-1], y_midpts[:-1]))[:, np.newaxis, :]\n",
    "    coord_mid = np.column_stack((x, y))[:, np.newaxis, :]\n",
    "    coord_end = np.column_stack((x_midpts[1:], y_midpts[1:]))[:, np.newaxis, :]\n",
    "    segments = np.concatenate((coord_start, coord_mid, coord_end), axis=1)\n",
    "\n",
    "    lc = LineCollection(segments, **default_kwargs)\n",
    "    lc.set_array(c)  # set the colors of each segment\n",
    "\n",
    "    return ax.add_collection(lc)\n",
    "\n",
    "\n",
    "# -------------- Create and show plot --------------\n",
    "# Some arbitrary function that gives x, y, and color values\n",
    "t = np.linspace(-7.4, -0.5, 200)\n",
    "x = 0.9 * np.sin(t)\n",
    "y = 0.9 * np.cos(1.6 * t)\n",
    "color = np.linspace(0, 2, t.size)\n",
    "\n",
    "# Create a figure and plot the line on it\n",
    "fig1, ax1 = plt.subplots()\n",
    "lines = colored_line(x, y, color, ax1, linewidth=10, cmap=\"plasma\")\n",
    "fig1.colorbar(lines)  # add a color legend\n",
    "# plt.colorbar(lines)\n",
    "\n",
    "# Set the axis limits and tick positions\n",
    "ax1.set_xlim(-1, 1)\n",
    "ax1.set_ylim(-1, 1)\n",
    "ax1.set_xticks((-1, 0, 1))\n",
    "ax1.set_yticks((-1, 0, 1))\n",
    "ax1.set_title(\"绘制变幻色彩的曲线\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0.98, '在散点图两侧使用直方图描述数据分布（用gridspec实现更精细的子图控制）')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Fixing random state for reproducibility\n",
    "np.random.seed(19680801)\n",
    "\n",
    "# some random data\n",
    "x = np.random.randn(1000)\n",
    "y = np.random.randn(1000)\n",
    "\n",
    "\n",
    "def scatter_hist(x, y, ax, ax_histx, ax_histy):\n",
    "    # no labels\n",
    "    ax_histx.tick_params(axis=\"x\", labelbottom=False)\n",
    "    ax_histy.tick_params(axis=\"y\", labelleft=False)\n",
    "\n",
    "    # the scatter plot:\n",
    "    ax.scatter(x, y)\n",
    "\n",
    "    # now determine nice limits by hand:\n",
    "    binwidth = 0.25\n",
    "    xymax = max(np.max(np.abs(x)), np.max(np.abs(y)))\n",
    "    lim = (int(xymax/binwidth) + 1) * binwidth\n",
    "\n",
    "    bins = np.arange(-lim, lim + binwidth, binwidth)\n",
    "    ax_histx.hist(x, bins=bins)\n",
    "    ax_histy.hist(y, bins=bins, orientation='horizontal')\n",
    "\n",
    "# Start with a square Figure.\n",
    "fig = plt.figure(figsize=(6, 6))\n",
    "# Add a gridspec with two rows and two columns and a ratio of 1 to 4 between\n",
    "# the size of the marginal Axes and the main Axes in both directions.\n",
    "# Also adjust the subplot parameters for a square plot.\n",
    "# gridspec能实现更精细的子图控制\n",
    "gs = fig.add_gridspec(2, 2,  width_ratios=(4, 1), height_ratios=(1, 4),\n",
    "                      left=0.1, right=0.9, bottom=0.1, top=0.9,\n",
    "                      wspace=0.05, hspace=0.05)\n",
    "# fig, axs = plt.subplots(2, 2, width_ratios=(4, 1), height_ratios=(1, 4))\n",
    "# Create the Axes.\n",
    "ax = fig.add_subplot(gs[1, 0])\n",
    "ax_histx = fig.add_subplot(gs[0, 0], sharex=ax)\n",
    "ax_histy = fig.add_subplot(gs[1, 1], sharey=ax)\n",
    "# ax = fig.add_subplot(axs[1, 0])\n",
    "# ax_histx = fig.add_subplot(axs[0, 0], sharex=ax)\n",
    "# ax_histy = fig.add_subplot(axs[1, 1], sharey=ax)\n",
    "# axs[0,1].set_visible(False)\n",
    "# Draw the scatter plot and marginals.\n",
    "scatter_hist(x, y, ax, ax_histx, ax_histy)\n",
    "fig.suptitle(\"在散点图两侧使用直方图描述数据分布（用gridspec实现更精细的子图控制）\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Fixing random state for reproducibility\n",
    "np.random.seed(19680801)\n",
    "\n",
    "\n",
    "N = 100\n",
    "r0 = 0.6\n",
    "x = 0.9 * np.random.rand(N)\n",
    "y = 0.9 * np.random.rand(N)\n",
    "area = (20 * np.random.rand(N))**2  # 0 to 10 point radii\n",
    "c = np.sqrt(area)\n",
    "r = np.sqrt(x ** 2 + y ** 2)\n",
    "# masked_where函数保留的是不满足条件的\n",
    "area1 = np.ma.masked_where(r < r0, area)\n",
    "area2 = np.ma.masked_where(r >= r0, area)\n",
    "# x1 = np.ma.masked_where(r < r0, x)\n",
    "# x2 = np.ma.masked_where(r >= r0, x)\n",
    "# y1 = np.ma.masked_where(r < r0, y)\n",
    "# y2 = np.ma.masked_where(r >= r0, y)\n",
    "# 半径大于等于r0的用三角形表示，小于r0的用圆圈表示\n",
    "plt.scatter(x, y, s=area2, marker='o', c=c, label='inside')\n",
    "plt.scatter(x, y, s=area1, marker='^', c=c, label='outside')\n",
    "# plt.scatter(x, y, s=area2, marker='o', label='inside')\n",
    "# Show the boundary between the regions:\n",
    "theta = np.arange(0, np.pi / 2, 0.01)\n",
    "plt.plot(r0 * np.cos(theta), r0 * np.sin(theta))\n",
    "plt.legend()\n",
    "plt.title(\"结合掩码进行散点\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.ticker as mticker\n",
    "year = [1950, 1960, 1970, 1980, 1990, 2000, 2010, 2018]\n",
    "population_by_continent = {\n",
    "    'Africa': [.228, .284, .365, .477, .631, .814, 1.044, 1.275],\n",
    "    'the Americas': [.340, .425, .519, .619, .727, .840, .943, 1.006],\n",
    "    'Asia': [1.394, 1.686, 2.120, 2.625, 3.202, 3.714, 4.169, 4.560],\n",
    "    'Europe': [.220, .253, .276, .295, .310, .303, .294, .293],\n",
    "    'Oceania': [.012, .015, .019, .022, .026, .031, .036, .039],\n",
    "}\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.stackplot(year, population_by_continent.values(),\n",
    "             labels=population_by_continent.keys(), alpha=0.8)\n",
    "ax.legend(loc='upper left')\n",
    "ax.set_title('堆叠图示例')\n",
    "ax.set_xlabel('Year')\n",
    "ax.set_ylabel('Number of people (billions)')\n",
    "# add tick at every 200 million people\n",
    "ax.yaxis.set_minor_locator(mticker.MultipleLocator(.2))\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "RGBA sequence should have length 3 or 4",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[49], line 45\u001b[0m\n\u001b[0;32m     42\u001b[0m ax\u001b[38;5;241m.\u001b[39mset(title\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMatplotlib release dates\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m     44\u001b[0m \u001b[38;5;66;03m# The vertical stems.\u001b[39;00m\n\u001b[1;32m---> 45\u001b[0m \u001b[43max\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvlines\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdates\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlevels\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m     46\u001b[0m \u001b[43m          \u001b[49m\u001b[43mcolor\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtab:red\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mis_feature\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrelease\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;241;43m.5\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mrelease\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mreleases\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     47\u001b[0m \u001b[38;5;66;03m# The baseline.\u001b[39;00m\n\u001b[0;32m     48\u001b[0m ax\u001b[38;5;241m.\u001b[39maxhline(\u001b[38;5;241m0\u001b[39m, c\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mblack\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\__init__.py:1423\u001b[0m, in \u001b[0;36m_preprocess_data.<locals>.inner\u001b[1;34m(ax, data, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1420\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mwraps(func)\n\u001b[0;32m   1421\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21minner\u001b[39m(ax, \u001b[38;5;241m*\u001b[39margs, data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m   1422\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m data \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m-> 1423\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43max\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43mmap\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43msanitize_sequence\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1425\u001b[0m     bound \u001b[38;5;241m=\u001b[39m new_sig\u001b[38;5;241m.\u001b[39mbind(ax, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m   1426\u001b[0m     auto_label \u001b[38;5;241m=\u001b[39m (bound\u001b[38;5;241m.\u001b[39marguments\u001b[38;5;241m.\u001b[39mget(label_namer)\n\u001b[0;32m   1427\u001b[0m                   \u001b[38;5;129;01mor\u001b[39;00m bound\u001b[38;5;241m.\u001b[39mkwargs\u001b[38;5;241m.\u001b[39mget(label_namer))\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\axes\\_axes.py:1166\u001b[0m, in \u001b[0;36mAxes.vlines\u001b[1;34m(self, x, ymin, ymax, colors, linestyles, label, **kwargs)\u001b[0m\n\u001b[0;32m   1163\u001b[0m lines \u001b[38;5;241m=\u001b[39m mcoll\u001b[38;5;241m.\u001b[39mLineCollection(masked_verts, colors\u001b[38;5;241m=\u001b[39mcolors,\n\u001b[0;32m   1164\u001b[0m                              linestyles\u001b[38;5;241m=\u001b[39mlinestyles, label\u001b[38;5;241m=\u001b[39mlabel)\n\u001b[0;32m   1165\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39madd_collection(lines, autolim\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[1;32m-> 1166\u001b[0m \u001b[43mlines\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_internal_update\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1168\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(x) \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m   1169\u001b[0m     \u001b[38;5;66;03m# Extreme values of x/ymin/ymax.  Using masked_verts here handles\u001b[39;00m\n\u001b[0;32m   1170\u001b[0m     \u001b[38;5;66;03m# the case of x being a masked *object* array (as can be generated\u001b[39;00m\n\u001b[0;32m   1171\u001b[0m     \u001b[38;5;66;03m# e.g. by errorbar()), which would make nanmin/nanmax stumble.\u001b[39;00m\n\u001b[0;32m   1172\u001b[0m     minx \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mnanmin(masked_verts[\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m, \u001b[38;5;241m0\u001b[39m])\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\artist.py:1186\u001b[0m, in \u001b[0;36mArtist._internal_update\u001b[1;34m(self, kwargs)\u001b[0m\n\u001b[0;32m   1179\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_internal_update\u001b[39m(\u001b[38;5;28mself\u001b[39m, kwargs):\n\u001b[0;32m   1180\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m   1181\u001b[0m \u001b[38;5;124;03m    Update artist properties without prenormalizing them, but generating\u001b[39;00m\n\u001b[0;32m   1182\u001b[0m \u001b[38;5;124;03m    errors as if calling `set`.\u001b[39;00m\n\u001b[0;32m   1183\u001b[0m \n\u001b[0;32m   1184\u001b[0m \u001b[38;5;124;03m    The lack of prenormalization is to maintain backcompatibility.\u001b[39;00m\n\u001b[0;32m   1185\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m-> 1186\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_update_props\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m   1187\u001b[0m \u001b[43m        \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;132;43;01m{cls.__name__}\u001b[39;49;00m\u001b[38;5;124;43m.set() got an unexpected keyword argument \u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\n\u001b[0;32m   1188\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;132;43;01m{prop_name!r}\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\artist.py:1162\u001b[0m, in \u001b[0;36mArtist._update_props\u001b[1;34m(self, props, errfmt)\u001b[0m\n\u001b[0;32m   1159\u001b[0m             \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mcallable\u001b[39m(func):\n\u001b[0;32m   1160\u001b[0m                 \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAttributeError\u001b[39;00m(\n\u001b[0;32m   1161\u001b[0m                     errfmt\u001b[38;5;241m.\u001b[39mformat(\u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mtype\u001b[39m(\u001b[38;5;28mself\u001b[39m), prop_name\u001b[38;5;241m=\u001b[39mk))\n\u001b[1;32m-> 1162\u001b[0m             ret\u001b[38;5;241m.\u001b[39mappend(\u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mv\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[0;32m   1163\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m ret:\n\u001b[0;32m   1164\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpchanged()\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\collections.py:1475\u001b[0m, in \u001b[0;36mLineCollection.set_color\u001b[1;34m(self, c)\u001b[0m\n\u001b[0;32m   1464\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mset_color\u001b[39m(\u001b[38;5;28mself\u001b[39m, c):\n\u001b[0;32m   1465\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m   1466\u001b[0m \u001b[38;5;124;03m    Set the edgecolor(s) of the LineCollection.\u001b[39;00m\n\u001b[0;32m   1467\u001b[0m \n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   1473\u001b[0m \u001b[38;5;124;03m        cycle through the sequence.\u001b[39;00m\n\u001b[0;32m   1474\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m-> 1475\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mset_edgecolor\u001b[49m\u001b[43m(\u001b[49m\u001b[43mc\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\collections.py:805\u001b[0m, in \u001b[0;36mCollection.set_edgecolor\u001b[1;34m(self, c)\u001b[0m\n\u001b[0;32m    803\u001b[0m     c \u001b[38;5;241m=\u001b[39m c\u001b[38;5;241m.\u001b[39mlower()\n\u001b[0;32m    804\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_original_edgecolor \u001b[38;5;241m=\u001b[39m c\n\u001b[1;32m--> 805\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_set_edgecolor\u001b[49m\u001b[43m(\u001b[49m\u001b[43mc\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\collections.py:784\u001b[0m, in \u001b[0;36mCollection._set_edgecolor\u001b[1;34m(self, c)\u001b[0m\n\u001b[0;32m    782\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstale \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[0;32m    783\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m\n\u001b[1;32m--> 784\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_edgecolors \u001b[38;5;241m=\u001b[39m \u001b[43mmcolors\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto_rgba_array\u001b[49m\u001b[43m(\u001b[49m\u001b[43mc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_alpha\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    785\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m set_hatch_color \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_edgecolors):\n\u001b[0;32m    786\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_hatch_color \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mtuple\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_edgecolors[\u001b[38;5;241m0\u001b[39m])\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\colors.py:485\u001b[0m, in \u001b[0;36mto_rgba_array\u001b[1;34m(c, alpha)\u001b[0m\n\u001b[0;32m    483\u001b[0m         rgba \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray(c)\n\u001b[0;32m    484\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m--> 485\u001b[0m         rgba \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray(\u001b[43m[\u001b[49m\u001b[43mto_rgba\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcc\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mcc\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mc\u001b[49m\u001b[43m]\u001b[49m)\n\u001b[0;32m    486\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m    487\u001b[0m     rgba \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray([to_rgba(cc) \u001b[38;5;28;01mfor\u001b[39;00m cc \u001b[38;5;129;01min\u001b[39;00m c])\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\colors.py:485\u001b[0m, in \u001b[0;36m<listcomp>\u001b[1;34m(.0)\u001b[0m\n\u001b[0;32m    483\u001b[0m         rgba \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray(c)\n\u001b[0;32m    484\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m--> 485\u001b[0m         rgba \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray([\u001b[43mto_rgba\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcc\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m cc \u001b[38;5;129;01min\u001b[39;00m c])\n\u001b[0;32m    486\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m    487\u001b[0m     rgba \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray([to_rgba(cc) \u001b[38;5;28;01mfor\u001b[39;00m cc \u001b[38;5;129;01min\u001b[39;00m c])\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\colors.py:299\u001b[0m, in \u001b[0;36mto_rgba\u001b[1;34m(c, alpha)\u001b[0m\n\u001b[0;32m    297\u001b[0m     rgba \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m    298\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m rgba \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:  \u001b[38;5;66;03m# Suppress exception chaining of cache lookup failure.\u001b[39;00m\n\u001b[1;32m--> 299\u001b[0m     rgba \u001b[38;5;241m=\u001b[39m \u001b[43m_to_rgba_no_colorcycle\u001b[49m\u001b[43m(\u001b[49m\u001b[43mc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43malpha\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    300\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m    301\u001b[0m         _colors_full_map\u001b[38;5;241m.\u001b[39mcache[c, alpha] \u001b[38;5;241m=\u001b[39m rgba\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\colors.py:383\u001b[0m, in \u001b[0;36m_to_rgba_no_colorcycle\u001b[1;34m(c, alpha)\u001b[0m\n\u001b[0;32m    381\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInvalid RGBA argument: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00morig_c\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m    382\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(c) \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m [\u001b[38;5;241m3\u001b[39m, \u001b[38;5;241m4\u001b[39m]:\n\u001b[1;32m--> 383\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRGBA sequence should have length 3 or 4\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m    384\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mall\u001b[39m(\u001b[38;5;28misinstance\u001b[39m(x, Number) \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m c):\n\u001b[0;32m    385\u001b[0m     \u001b[38;5;66;03m# Checks that don't work: `map(float, ...)`, `np.array(..., float)` and\u001b[39;00m\n\u001b[0;32m    386\u001b[0m     \u001b[38;5;66;03m# `np.array(...).astype(float)` would all convert \"0.5\" to 0.5.\u001b[39;00m\n\u001b[0;32m    387\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInvalid RGBA argument: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00morig_c\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n",
      "\u001b[1;31mValueError\u001b[0m: RGBA sequence should have length 3 or 4"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error in callback <function _draw_all_if_interactive at 0x000001DED3F5D940> (for post_execute), with arguments args (),kwargs {}:\n"
     ]
    },
    {
     "ename": "ValueError",
     "evalue": "RGBA sequence should have length 3 or 4",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\pyplot.py:119\u001b[0m, in \u001b[0;36m_draw_all_if_interactive\u001b[1;34m()\u001b[0m\n\u001b[0;32m    117\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_draw_all_if_interactive\u001b[39m():\n\u001b[0;32m    118\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m matplotlib\u001b[38;5;241m.\u001b[39mis_interactive():\n\u001b[1;32m--> 119\u001b[0m         \u001b[43mdraw_all\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\_pylab_helpers.py:132\u001b[0m, in \u001b[0;36mGcf.draw_all\u001b[1;34m(cls, force)\u001b[0m\n\u001b[0;32m    130\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m manager \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39mget_all_fig_managers():\n\u001b[0;32m    131\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m force \u001b[38;5;129;01mor\u001b[39;00m manager\u001b[38;5;241m.\u001b[39mcanvas\u001b[38;5;241m.\u001b[39mfigure\u001b[38;5;241m.\u001b[39mstale:\n\u001b[1;32m--> 132\u001b[0m         \u001b[43mmanager\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcanvas\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdraw_idle\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\backend_bases.py:2054\u001b[0m, in \u001b[0;36mFigureCanvasBase.draw_idle\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m   2052\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_is_idle_drawing:\n\u001b[0;32m   2053\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_idle_draw_cntx():\n\u001b[1;32m-> 2054\u001b[0m         \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdraw\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\backends\\backend_agg.py:405\u001b[0m, in \u001b[0;36mFigureCanvasAgg.draw\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    401\u001b[0m \u001b[38;5;66;03m# Acquire a lock on the shared font cache.\u001b[39;00m\n\u001b[0;32m    402\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m RendererAgg\u001b[38;5;241m.\u001b[39mlock, \\\n\u001b[0;32m    403\u001b[0m      (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtoolbar\u001b[38;5;241m.\u001b[39m_wait_cursor_for_draw_cm() \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtoolbar\n\u001b[0;32m    404\u001b[0m       \u001b[38;5;28;01melse\u001b[39;00m nullcontext()):\n\u001b[1;32m--> 405\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfigure\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdraw\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrenderer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    406\u001b[0m     \u001b[38;5;66;03m# A GUI class may be need to update a window using this draw, so\u001b[39;00m\n\u001b[0;32m    407\u001b[0m     \u001b[38;5;66;03m# don't forget to call the superclass.\u001b[39;00m\n\u001b[0;32m    408\u001b[0m     \u001b[38;5;28msuper\u001b[39m()\u001b[38;5;241m.\u001b[39mdraw()\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\artist.py:74\u001b[0m, in \u001b[0;36m_finalize_rasterization.<locals>.draw_wrapper\u001b[1;34m(artist, renderer, *args, **kwargs)\u001b[0m\n\u001b[0;32m     72\u001b[0m \u001b[38;5;129m@wraps\u001b[39m(draw)\n\u001b[0;32m     73\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdraw_wrapper\u001b[39m(artist, renderer, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m---> 74\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[43mdraw\u001b[49m\u001b[43m(\u001b[49m\u001b[43martist\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     75\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m renderer\u001b[38;5;241m.\u001b[39m_rasterizing:\n\u001b[0;32m     76\u001b[0m         renderer\u001b[38;5;241m.\u001b[39mstop_rasterizing()\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\artist.py:51\u001b[0m, in \u001b[0;36mallow_rasterization.<locals>.draw_wrapper\u001b[1;34m(artist, renderer)\u001b[0m\n\u001b[0;32m     48\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m artist\u001b[38;5;241m.\u001b[39mget_agg_filter() \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m     49\u001b[0m         renderer\u001b[38;5;241m.\u001b[39mstart_filter()\n\u001b[1;32m---> 51\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mdraw\u001b[49m\u001b[43m(\u001b[49m\u001b[43martist\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     52\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[0;32m     53\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m artist\u001b[38;5;241m.\u001b[39mget_agg_filter() \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\figure.py:3071\u001b[0m, in \u001b[0;36mFigure.draw\u001b[1;34m(self, renderer)\u001b[0m\n\u001b[0;32m   3068\u001b[0m         \u001b[38;5;66;03m# ValueError can occur when resizing a window.\u001b[39;00m\n\u001b[0;32m   3070\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpatch\u001b[38;5;241m.\u001b[39mdraw(renderer)\n\u001b[1;32m-> 3071\u001b[0m \u001b[43mmimage\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_draw_list_compositing_images\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m   3072\u001b[0m \u001b[43m    \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43martists\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msuppressComposite\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   3074\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m sfig \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msubfigs:\n\u001b[0;32m   3075\u001b[0m     sfig\u001b[38;5;241m.\u001b[39mdraw(renderer)\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\image.py:131\u001b[0m, in \u001b[0;36m_draw_list_compositing_images\u001b[1;34m(renderer, parent, artists, suppress_composite)\u001b[0m\n\u001b[0;32m    129\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m not_composite \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m has_images:\n\u001b[0;32m    130\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m artists:\n\u001b[1;32m--> 131\u001b[0m         \u001b[43ma\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdraw\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    132\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m    133\u001b[0m     \u001b[38;5;66;03m# Composite any adjacent images together\u001b[39;00m\n\u001b[0;32m    134\u001b[0m     image_group \u001b[38;5;241m=\u001b[39m []\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\artist.py:51\u001b[0m, in \u001b[0;36mallow_rasterization.<locals>.draw_wrapper\u001b[1;34m(artist, renderer)\u001b[0m\n\u001b[0;32m     48\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m artist\u001b[38;5;241m.\u001b[39mget_agg_filter() \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m     49\u001b[0m         renderer\u001b[38;5;241m.\u001b[39mstart_filter()\n\u001b[1;32m---> 51\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mdraw\u001b[49m\u001b[43m(\u001b[49m\u001b[43martist\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     52\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[0;32m     53\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m artist\u001b[38;5;241m.\u001b[39mget_agg_filter() \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\axes\\_base.py:3107\u001b[0m, in \u001b[0;36m_AxesBase.draw\u001b[1;34m(self, renderer)\u001b[0m\n\u001b[0;32m   3104\u001b[0m         a\u001b[38;5;241m.\u001b[39mdraw(renderer)\n\u001b[0;32m   3105\u001b[0m     renderer\u001b[38;5;241m.\u001b[39mstop_rasterizing()\n\u001b[1;32m-> 3107\u001b[0m \u001b[43mmimage\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_draw_list_compositing_images\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m   3108\u001b[0m \u001b[43m    \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43martists\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfigure\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msuppressComposite\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   3110\u001b[0m renderer\u001b[38;5;241m.\u001b[39mclose_group(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124maxes\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m   3111\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstale \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\image.py:131\u001b[0m, in \u001b[0;36m_draw_list_compositing_images\u001b[1;34m(renderer, parent, artists, suppress_composite)\u001b[0m\n\u001b[0;32m    129\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m not_composite \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m has_images:\n\u001b[0;32m    130\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m artists:\n\u001b[1;32m--> 131\u001b[0m         \u001b[43ma\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdraw\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    132\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m    133\u001b[0m     \u001b[38;5;66;03m# Composite any adjacent images together\u001b[39;00m\n\u001b[0;32m    134\u001b[0m     image_group \u001b[38;5;241m=\u001b[39m []\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\artist.py:51\u001b[0m, in \u001b[0;36mallow_rasterization.<locals>.draw_wrapper\u001b[1;34m(artist, renderer)\u001b[0m\n\u001b[0;32m     48\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m artist\u001b[38;5;241m.\u001b[39mget_agg_filter() \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m     49\u001b[0m         renderer\u001b[38;5;241m.\u001b[39mstart_filter()\n\u001b[1;32m---> 51\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mdraw\u001b[49m\u001b[43m(\u001b[49m\u001b[43martist\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     52\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[0;32m     53\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m artist\u001b[38;5;241m.\u001b[39mget_agg_filter() \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\collections.py:350\u001b[0m, in \u001b[0;36mCollection.draw\u001b[1;34m(self, renderer)\u001b[0m\n\u001b[0;32m    347\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m\n\u001b[0;32m    348\u001b[0m renderer\u001b[38;5;241m.\u001b[39mopen_group(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mget_gid())\n\u001b[1;32m--> 350\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mupdate_scalarmappable\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    352\u001b[0m transform, offset_trf, offsets, paths \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_prepare_points()\n\u001b[0;32m    354\u001b[0m gc \u001b[38;5;241m=\u001b[39m renderer\u001b[38;5;241m.\u001b[39mnew_gc()\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\collections.py:900\u001b[0m, in \u001b[0;36mCollection.update_scalarmappable\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    898\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_edgecolors \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_mapped_colors\n\u001b[0;32m    899\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m--> 900\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_set_edgecolor\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_original_edgecolor\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    901\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstale \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\collections.py:784\u001b[0m, in \u001b[0;36mCollection._set_edgecolor\u001b[1;34m(self, c)\u001b[0m\n\u001b[0;32m    782\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstale \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[0;32m    783\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m\n\u001b[1;32m--> 784\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_edgecolors \u001b[38;5;241m=\u001b[39m \u001b[43mmcolors\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto_rgba_array\u001b[49m\u001b[43m(\u001b[49m\u001b[43mc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_alpha\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    785\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m set_hatch_color \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_edgecolors):\n\u001b[0;32m    786\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_hatch_color \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mtuple\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_edgecolors[\u001b[38;5;241m0\u001b[39m])\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\colors.py:485\u001b[0m, in \u001b[0;36mto_rgba_array\u001b[1;34m(c, alpha)\u001b[0m\n\u001b[0;32m    483\u001b[0m         rgba \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray(c)\n\u001b[0;32m    484\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m--> 485\u001b[0m         rgba \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray(\u001b[43m[\u001b[49m\u001b[43mto_rgba\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcc\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mcc\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mc\u001b[49m\u001b[43m]\u001b[49m)\n\u001b[0;32m    486\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m    487\u001b[0m     rgba \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray([to_rgba(cc) \u001b[38;5;28;01mfor\u001b[39;00m cc \u001b[38;5;129;01min\u001b[39;00m c])\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\colors.py:485\u001b[0m, in \u001b[0;36m<listcomp>\u001b[1;34m(.0)\u001b[0m\n\u001b[0;32m    483\u001b[0m         rgba \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray(c)\n\u001b[0;32m    484\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m--> 485\u001b[0m         rgba \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray([\u001b[43mto_rgba\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcc\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m cc \u001b[38;5;129;01min\u001b[39;00m c])\n\u001b[0;32m    486\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m    487\u001b[0m     rgba \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray([to_rgba(cc) \u001b[38;5;28;01mfor\u001b[39;00m cc \u001b[38;5;129;01min\u001b[39;00m c])\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\colors.py:299\u001b[0m, in \u001b[0;36mto_rgba\u001b[1;34m(c, alpha)\u001b[0m\n\u001b[0;32m    297\u001b[0m     rgba \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m    298\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m rgba \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:  \u001b[38;5;66;03m# Suppress exception chaining of cache lookup failure.\u001b[39;00m\n\u001b[1;32m--> 299\u001b[0m     rgba \u001b[38;5;241m=\u001b[39m \u001b[43m_to_rgba_no_colorcycle\u001b[49m\u001b[43m(\u001b[49m\u001b[43mc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43malpha\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    300\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m    301\u001b[0m         _colors_full_map\u001b[38;5;241m.\u001b[39mcache[c, alpha] \u001b[38;5;241m=\u001b[39m rgba\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\matplotlib\\colors.py:383\u001b[0m, in \u001b[0;36m_to_rgba_no_colorcycle\u001b[1;34m(c, alpha)\u001b[0m\n\u001b[0;32m    381\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInvalid RGBA argument: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00morig_c\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m    382\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(c) \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m [\u001b[38;5;241m3\u001b[39m, \u001b[38;5;241m4\u001b[39m]:\n\u001b[1;32m--> 383\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRGBA sequence should have length 3 or 4\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m    384\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mall\u001b[39m(\u001b[38;5;28misinstance\u001b[39m(x, Number) \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m c):\n\u001b[0;32m    385\u001b[0m     \u001b[38;5;66;03m# Checks that don't work: `map(float, ...)`, `np.array(..., float)` and\u001b[39;00m\n\u001b[0;32m    386\u001b[0m     \u001b[38;5;66;03m# `np.array(...).astype(float)` would all convert \"0.5\" to 0.5.\u001b[39;00m\n\u001b[0;32m    387\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInvalid RGBA argument: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00morig_c\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n",
      "\u001b[1;31mValueError\u001b[0m: RGBA sequence should have length 3 or 4"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 880x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "import matplotlib.dates as mdates\n",
    "\n",
    "\n",
    "\n",
    "# In case the above fails, e.g. because of missing internet connection\n",
    "# use the following lists as fallback.\n",
    "releases = ['2.2.4', '3.0.3', '3.0.2', '3.0.1', '3.0.0', '2.2.3',\n",
    "            '2.2.2', '2.2.1', '2.2.0', '2.1.2', '2.1.1', '2.1.0',\n",
    "            '2.0.2', '2.0.1', '2.0.0', '1.5.3', '1.5.2', '1.5.1',\n",
    "            '1.5.0', '1.4.3', '1.4.2', '1.4.1', '1.4.0']\n",
    "dates = ['2019-02-26', '2019-02-26', '2018-11-10', '2018-11-10',\n",
    "            '2018-09-18', '2018-08-10', '2018-03-17', '2018-03-16',\n",
    "            '2018-03-06', '2018-01-18', '2017-12-10', '2017-10-07',\n",
    "            '2017-05-10', '2017-05-02', '2017-01-17', '2016-09-09',\n",
    "            '2016-07-03', '2016-01-10', '2015-10-29', '2015-02-16',\n",
    "            '2014-10-26', '2014-10-18', '2014-08-26']\n",
    "\n",
    "dates = [datetime.strptime(d, \"%Y-%m-%d\") for d in dates]  # Convert strs to dates.\n",
    "releases = [tuple(release.split('.')) for release in releases]  # Split by component.\n",
    "dates, releases = zip(*sorted(zip(dates, releases)))  # Sort by increasing date.\n",
    "\n",
    "# Choose some nice levels: alternate meso releases between top and bottom, and\n",
    "# progressively shorten the stems for micro releases.\n",
    "levels = []\n",
    "macro_meso_releases = sorted({release[:2] for release in releases})\n",
    "for release in releases:\n",
    "    macro_meso = release[:2]\n",
    "    micro = int(release[2])\n",
    "    h = 1 + 0.8 * (5 - micro)\n",
    "    level = h if macro_meso_releases.index(macro_meso) % 2 == 0 else -h\n",
    "    levels.append(level)\n",
    "\n",
    "\n",
    "def is_feature(release):\n",
    "    \"\"\"Return whether a version (split into components) is a feature release.\"\"\"\n",
    "    return release[-1] == '0'\n",
    "\n",
    "\n",
    "# The figure and the axes.\n",
    "fig, ax = plt.subplots(figsize=(8.8, 4), layout=\"constrained\")\n",
    "ax.set(title=\"Matplotlib release dates\")\n",
    "\n",
    "# The vertical stems.\n",
    "ax.vlines(dates, 0, levels,\n",
    "          color=[(\"tab:red\", 1 if is_feature(release) else .5) for release in releases])\n",
    "# The baseline.\n",
    "ax.axhline(0, c=\"black\")\n",
    "# The markers on the baseline.\n",
    "meso_dates = [date for date, release in zip(dates, releases) if is_feature(release)]\n",
    "micro_dates = [date for date, release in zip(dates, releases)\n",
    "               if not is_feature(release)]\n",
    "ax.plot(micro_dates, np.zeros_like(micro_dates), \"ko\", mfc=\"white\")\n",
    "ax.plot(meso_dates, np.zeros_like(meso_dates), \"ko\", mfc=\"tab:red\")\n",
    "\n",
    "# Annotate the lines.\n",
    "for date, level, release in zip(dates, levels, releases):\n",
    "    version_str = '.'.join(release)\n",
    "    ax.annotate(version_str, xy=(date, level),\n",
    "                xytext=(-3, np.sign(level)*3), textcoords=\"offset points\",\n",
    "                verticalalignment=\"bottom\" if level > 0 else \"top\",\n",
    "                weight=\"bold\" if is_feature(release) else \"normal\",\n",
    "                bbox=dict(boxstyle='square', pad=0, lw=0, fc=(1, 1, 1, 0.7)))\n",
    "\n",
    "ax.xaxis.set(major_locator=mdates.YearLocator(),\n",
    "             major_formatter=mdates.DateFormatter(\"%Y\"))\n",
    "\n",
    "# Remove the y-axis and some spines.\n",
    "ax.yaxis.set_visible(False)\n",
    "ax.spines[[\"left\", \"top\", \"right\"]].set_visible(False)\n",
    "\n",
    "ax.margins(y=0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: xlabel='carat', ylabel='price'>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 650x650 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "sns.set_theme(style=\"whitegrid\")\n",
    "\n",
    "# Load the example diamonds dataset\n",
    "diamonds = sns.load_dataset(\"diamonds\")\n",
    "\n",
    "# Draw a scatter plot while assigning point colors and sizes to different\n",
    "# variables in the dataset\n",
    "f, ax = plt.subplots(figsize=(6.5, 6.5))\n",
    "# despine用于去掉图中上方和右边的坐标轴\n",
    "sns.despine(f, left=True, bottom=True)\n",
    "clarity_ranking = [\"I1\", \"SI2\", \"SI1\", \"VS2\", \"VS1\", \"VVS2\", \"VVS1\", \"IF\"]\n",
    "\n",
    "\"\"\"\n",
    "seaborn的scatterplot传入的是pandas的dataframe或numpy数组（变量名为data），\n",
    "x，y既可以传入向量，也可以传入data中的键（字符串），hue用于指定点的色调依赖的指标，\n",
    "size指定点的大小依赖的指标，hue_order指定色调语义分类级别的处理和绘图顺序\n",
    "\"\"\"\n",
    "sns.scatterplot(x=\"carat\", y=\"price\",\n",
    "                hue=\"clarity\", size=\"depth\",\n",
    "                palette=\"ch:r=-.2,d=.3_r\",\n",
    "                hue_order=clarity_ranking,\n",
    "                sizes=(1, 8), linewidth=0,\n",
    "                data=diamonds, ax=ax)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
